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SPIRES-BOOKS: FIND KEYWORD PUBLIC HEALTH *END*INIT* use /tmp/qspiwww.webspi1/5295.43 QRY 131.225.70.96 . find keyword public health ( in books using www
Call number:42-USC-9601 Show nearby items on shelf
Title:CERCLA / SARA: Comprehensive Environmental Response, Compensatio$ TITLE-VARIANT = THE PUBLIC HEALTH AND WELFARE CHAPTER 103--COMPREHENSIVE$ FULLTEXT = https://www.epw.senate.gov/cercla.pdf
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Note:42 USC 9601
Series:WorkSmart Standard
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Call number:1118964357:ONLINE Show nearby items on shelf
Title:Spatial Agent-Based Simulation Modeling in Public Health: Design, Implementation, and Applications for Malaria Epidemiology
Author(s): Arifin
Date:2016
Publisher:Wiley
Size:1 online resource (321 p.)
ISBN:9781118964354
Series:eBooks
Series:Wiley Online Library
Series:Wiley 2016 package purchase
Keywords: Statistics
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Call number:0471387711:ONLINE Show nearby items on shelf
Title:Applied Spatial Statistics of Public Health Data
Author(s): Waller
Date:2004
Publisher:Wiley-Interscience
Size:1 online resource (521 p.)
ISBN:9780471387718
Series:eBooks
Series:Wiley Online Library
Series:Wiley 2016 package purchase
Keywords: Statistics
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Call number:0470092483:ONLINE Show nearby items on shelf
Title:Spatial and Syndromic Surveillance for Public Health
Author(s): Lawson
Date:2005
Publisher:Wiley
Size:1 online resource (285 p.)
ISBN:9780470092484
Series:eBooks
Series:Wiley Online Library
Series:Wiley 2016 package purchase
Keywords: Statistics
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Call number:0470068124:ONLINE Show nearby items on shelf
Title:Disease Surveillance: A Public Health Informatics Approach
Author(s): Lombardo
Date:2007
Publisher:Wiley-Interscience
Size:1 online resource (489 p.)
ISBN:9780470068120
Series:eBooks
Series:Wiley Online Library
Series:Wiley 2016 package purchase
Keywords: Statistics
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Call number:TK9360.F751 Show nearby items on shelf
Title:The nuclear fuel cycle : a survey of the public health, environmental and national security effects of nuclear power
Author(s): Union of Concerned Scientists
Daniel F. Ford
Date:1973
Publisher:Union of Concerned Scientists, Cambridge, Mass
Size:207
Keywords: Atomic energy industries.
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Call number:SPRINGER-2016-9789811008719:ONLINE Show nearby items on shelf
Title:Complex Surveys Analysis of Categorical Data
Author(s): Parimal Mukhopadhyay
Date:2016
Size:1 online resource (248 p.)
Note:10.1007/978-981-10-0871-9
Contents:Chapter 1. Preliminaries -- Chapter 2. The Design-Effects and Mis-Specification Effects -- Chapter 3. Some Classical Models in Categorical Data Analysis -- Chapter 4. Analysis of Categorical Data under a Full Model -- Chapter 5. Analysis of Catego rical Data under Log-Linear Models -- Chapter 6. Analysis of Categorical Data under Logistic Regression Model -- Chapter 7. Analysis in the Presence of Classification Errors -- Chapter 8. Approximate MLE’s from Survey Data
ISBN:9789811008719
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Statistics , Statistics , Statistical Theory and Methods , Statistics for Business/Economics/Mathematical Finance/Insurance , Statistics for Life Sciences, Medicine, Health Sciences , Statistics for Social Science, Behavorial Science, Education, Public Policy, and
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Call number:SPRINGER-2016-9784431559009:ONLINE Show nearby items on shelf
Title:Group-Sequential Clinical Trials with Multiple Co-Objectives
Author(s): Toshimitsu Hamasaki
Date:2016
Size:1 online resource (113 p.)
Note:10.1007/978-4-431-55900-9
Contents:1. Introduction -- 2. Early Stopping for Efficacy in Clinical Trials with multiple co-primary endpoints -- 3. Sample size recalculation based on observed effects at interim -- 4. Early stopping for futility in Clinical Trials with multiple co-prima ry endpoints -- 5. Early stopping for futility or Efficacy in Clinical Trials with multiple co-primary endpoints -- 6. Clinical Trials with multiple primary endpoints -- 7. Group-sequential designs for three-arm noninferiority clinical trials -- 8. Furthe r development: topics not covered in this book
ISBN:9784431559009
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Statistics , Statistics , Statistical Theory and Methods , Statistics for Life Sciences, Medicine, Health Sciences , Statistics for Social Science, Behavorial Science, Education, Public Policy, and
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Call number:SPRINGER-2016-9783319404134:ONLINE Show nearby items on shelf
Title:Mathematical and Statistical Modeling for Emerging and Re-emerging Infectious Diseases
Author(s):
Date:2016
Size:1 online resource (63 p.)
Note:10.1007/978-3-319-40413-4
Contents:Preface -- A Reality of Its Own -- Modeling the Impact of Behavior Change on the Spread of Ebola -- A model for coupled outbreaks contained by behavior change -- Real-time assessment of the international spreading risk associated with the 2014 West African Ebola Outbreak -- Modeling the case of early detection of Ebola virus disease -- Modeling ring vaccination strategies to control Ebola virus disease epidemics -- Estimation of the number of sickbeds during Ebola epidemics using optimal control the ory -- Inverse problems and Ebola virus disease using an age of infection model -- Assessing the Efficiency of Movement -- Restriction as a Control Strategy of Ebola -- Patch models of EVD transmission dynamics -- From bee species aggregation to models of disease avoidance: The \emph{Ben-Hur} effect} -- Designing Public Health Policies to Mitigate the Adverse Consequences of Rural-Urban Migration via Meta-Population Modeling -- Age of Infection Epidemic Models -- Optimal Control of
Vaccination in an Age-Structured Cholera Model -- A Multi-risk Model for Understanding the Spread of Chlamydia -- The 1997 Measles Outbreak in Metropolitan São Paulo, Brazil: Strategic Implications of Increasing Urbanization -- Methods to determine the end of an infectious disease epidemic: A short review -- Statistical considerations in infectious disease randomized controlled trials -- Epidemic models with and without mortality: when does it matter?- Capturing Household Transmission in Compartmen tal Models of Infectious Disease -- Bistable endemic states in a Susceptible-Infectious-Susceptible model with behavior-dependent Vaccination -- Index
ISBN:9783319404134
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Mathematics , Infectious diseases , Epidemiology , Probabilities , Statistics , Mathematics , Probability Theory and Stochastic Processes , Infectious Diseases , Statistics for Life Sciences, Medicine, Health Sciences , Epidemiology
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Call number:SPRINGER-2016-9783319281582:ONLINE Show nearby items on shelf
Title:Modeling Discrete Time-to-Event Data
Author(s): Gerhard Tutz
Date:2016
Size:1 online resource (3 p.)
Note:10.1007/978-3-319-28158-2
Contents:Introduction -- The Life Table -- Basic Regression Models -- Evaluation and Model Choice -- Nonparametric Modelling and Smooth Effects -- Tree-Based Approaches -- High-Dimensional Models - Structuring and Selection of Predictors -- Competing Risks Models -- Multiple-Spell Analysis -- Frailty Models and Heterogeneity -- Multiple-Spell Analysis -- List of Examples -- Bibliography -- Subject Index -- Author Index
ISBN:9783319281582
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Statistics , Statistics , Statistical Theory and Methods , Statistics for Life Sciences, Medicine, Health Sciences , Statistics for Social Science, Behavorial Science, Education, Public Policy, and , Statistics and Computing/Statistics Programs
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Call number:SPRINGER-2016-9783319272740:ONLINE Show nearby items on shelf
Title:Topics in Theoretical and Applied Statistics
Author(s):
Date:2016
Size:1 online resource (18 p.)
Note:10.1007/978-3-319-27274-0
Contents:Part I Statistical Theory and Methods -- Part II Data Mining and Multivariate Data Analysis -- Part III Sampling and Estimation Methods -- Part IV Social Statistics, Demography and Health Data -- Part V Economic Statistics and Econometrics.
ISBN:9783319272740
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Statistics , Demography , Statistics , Statistical Theory and Methods , Statistics for Business/Economics/Mathematical Finance/Insurance , Statistics for Social Science, Behavorial Science, Education, Public Policy, and , Demography
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Call number:SPRINGER-2016-9783319235585:ONLINE Show nearby items on shelf
Title:Nonclinical Statistics for Pharmaceutical and Biotechnology Industries
Author(s):
Date:2016
Edition:1st ed. 2016
Size:1 online resource (113 p.)
Note:10.1007/978-3-319-23558-5
Contents:Introduction to Nonclinical Statistics for Pharmaceutical and Biotechnology Industries -- Regulatory Nonclinical Statistics -- How to be a good nonclinical statistician -- Statistical Methods for Drug Discovery -- High-throughput Screening Data Anal ysis -- Quantitative-Structure Activity Relationship Modeling and Cheminformatics -- GWAS for Drug Discovery -- Statistical applications in Design and Analysis of In-Vitro Safety Screening Assays -- Nonclinical safety assessment: an introduction for stati sticians -- General Toxicology, Safety Pharmacology, Reproductive Toxicology and Juvenile Toxicology Studies -- Clinical Assays for Biological Macromolecules -- Recent Research Projects by FDA's Pharmacology and Toxicology Statistics Team -- Design and ev aluation of drug combination studies -- Biomarkers -- Overview of Drug Development and Statistical Tools for Manufacturing and Testing -- Assay Validation -- Lifecycle Approach to Bioassay -- Quality by Design: Building Quality into
Products and Processes -- Process Validation -- Acceptance Sampling -- Process Capability and Statistical Process Control -- Statistical Considerations for Stability and the Estimation of Shelf Life.- In Vitro Dissolution Testing: Statistical Approa ches and Issues -- Assessing Content Uniformity -- Chemometrics and Predictive Modelling -- Statistical Methods for Comparability Studies
ISBN:9783319235585
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Statistics , Pharmacology , Medicine , Statistics , Statistics for Life Sciences, Medicine, Health Sciences , Medicine/Public Health, general , Pharmacology/Toxicology
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Call number:SPRINGER-2014-9781461461340:ONLINE Show nearby items on shelf
Title:Empirical Agent-Based Modelling - Challenges and Solutions [electronic resource] : Volume 1, The Characterisation and Parameterisation of Empirical Agent-Based Models
Author(s): Alexander Smajgl
Olivier Barreteau
Date:2014
Publisher:New York, NY : Springer New York : Imprint: Springer
Size:1 online resource
Note:This instructional bookshowcases techniques to parameterise human agents in empirical agent-based models(ABM). In doing so, it provides a timely overview of key ABM methodologies and the most innovative approaches through avariety of empirical applic ations. It features cutting-edge research from leading academics and practitioners, and will provide a guide for characterising and parameterising human agents in empirical ABM.In order to facilitatelearning, this text shares the valuable experiences of o ther modellers in particular modelling situations. Very little has been published in the area of empirical ABM, and this contributed volume will appeal to graduate-level studentsand researchers studying simulation modeling in economics, sociology, ecology , and trans-disciplinary studies, such as topics related to sustainability. In a similar vein to the instruction found in a cookbook, this text provides theempirical modeller with a set of 'recipes' ready to be implemented. Agent-based modeling (ABM) is a powerful, simulation-modeling technique that has seen a dramatic increase in real-world applications in recent years. In ABM, asystem is modeled as a collection of autonomous decision-making entities called agents. Each agent individually assesses its si tuation and makes decisions on the basis of a set of rules. Agents may execute various behaviorsappropriate for the system they representfor example, producing, consuming, or selling. ABM is increasingly used for simulating real-world systems, such as nat ural resource use, transportation, public health, andconflict.Decision makers increasingly demand support that covers a multitude of indicators that can be effectively addressed using ABM. This is especially the case in situations where human behavior is identified as a criticalelement. As a result, ABM will only continue its rapid growth. This is the first volume in a series of books that aims to contribute to a cultural chan
Contents:Empiricism and agent based modelling
A case study on characterising and parameterising an agent based integrated model of recreational fishing and coral reef ecosystem dynamics
An Agent Based Model of Tourist Movements in New Zealand
Humanecosystem interaction in large ensemble model systems
Using Spatially Explicit Marketing Data to Build Social Simulations
ISBN:9781461461340
Series:eBooks
Series:SpringerLink
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Computer simulation , Mathematical statistics
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Call number:SPRINGER-2013-9789400770034:ONLINE Show nearby items on shelf
Title:Advanced Sensors for Safety and Security [electronic resource]
Author(s): Ashok Vaseashta
Surik Khudaverdyan
Date:2013
Publisher:Dordrecht : Springer Netherlands : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:This book results from a NATO Advanced Research Workshop titled Technological Innovations in CBRNE Sensing and Detection for Safety, Security, and Sustainability held in Yerevan, Armenia in 2012. The objective was todiscuss and exchange views as to h ow fusion of advanced technologies can lead to improved sensors/detectors in support of defense, security, and situational awareness. The chapters range from policy and implementation, advanced sensorplatforms using stand-off (THz and optical) and point-c ontact methods for detection of chemical, nuclear, biological, nuclear and explosive agents and contaminants in water, to synthesis methods for several materials used for sensors.In view of asymmetric, kinetic, and distributed nature of threat vectors, an emphasis is placed to examine new generation of sensors/detectors that utilize an ecosystems of innovation and advanced sciences convergence in support ofeffective counter-measures against CBRNE threats. The book will be of considerable interest and valu e to those already pursuing or considering careers in the field of nanostructured materials, and sensing/detection of CBRNE agentsand water-borne contaminants. For policy implementation and compliance standpoint, the book serves as a resource of several i nformative contributions. In general, it serves as a valuable source of information for those interested inhow nanomaterials and nanotechnologies are advancing the field of sensing and detection using nexus of advanced technologies for scientists, technol ogists, policy makers, and soldiers and commanders
Note:Springer eBooks
Contents:Preface
Part I. Invited and Key Lectures
Challenges and Opportunities
Ecosystem of Innovations using Nanomaterials based CBRNE Sensors and Threat Mitigation
New Terahertz Security Opportunities Based on Nanometric Technology
Structured Inorganic Oxide
Based Materials for the Absorption and Destruction of CBRN Agents
The Quirra Syndrome: Matter of Translational Medicine
Part II. Policy, Diplomacy, Verification, Compliance, Implementation
The Yin and Yang of Countering Biological Threats: Public Health And Security Under The International Health Regulations, Biological Wea
ISBN:9789400770034
Series:e-books
Series:SpringerLink (Online service)
Series:NATO Science for Peace and Security Series B: Physics and Biophysics, 1874-6500
Series:Physics and Astronomy (Springer-11651)
Keywords: Environmental sciences , Engineering , Environmental pollution
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Call number:SPRINGER-2013-9781461476184:ONLINE Show nearby items on shelf
Title:Applied Spatial Data Analysis with R [electronic resource]
Author(s): Roger S Bivand
Edzer Pebesma
Virgilio Gmez-Rubio
Date:2013
Edition:2nd ed. 2013
Publisher:New York, NY : Springer New York : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Applied Spatial Data Analysis with R, Second Edition, is divided into two basic parts, the first presenting R packages, functions, classes and methods for handling spatial data. This part is of interest to users who need to accessand visualise spatia l data. Data import and export for many file formats for spatial data are covered in detail, as is the interface between R and the open source GRASS GIS and the handling of spatio-temporal data. The second partshowcases more specialised kinds of spatial d ata analysis, including spatial point pattern analysis, interpolation and geostatistics, areal data analysis and disease mapping. The coverage of methods of spatial data analysis ranges fromstandard techniques to new developments, and the examples used ar e largely taken from the spatial statistics literature. All the examples can be run using R contributed packages available from the CRAN website, with code and additionaldata sets from the book's own website. Compared to the first edition, the second edit ion covers the more systematic approach towards handling spatial data in R, as well as a number of important and widely used CRAN packages that haveappeared since the first edition. This book will be of interest to researchers who intend to use R to hand le, visualise, and analyse spatial data. It will also be of interest to spatial data analysts who do not use R, but who areinterested in practical aspects of implementing software for spatial data analysis. It is a suitable companion book for introductory spatial statistics courses and for applied methods courses in a wide range of subjects using spatialdata, including human and physical geography, geographical information science and geoinformatics, the environmental sciences, ecology, public health and disease control, economics, public administration and political science. Thebook has a website where complete code examples, data sets, and other support material may be found: http://www.asdar-boo
Note:Springer eBooks
Contents:Preface 2nd edition
Preface 1st edition
Hello World: Introducing Spatial Data
Classes for Spatial Data in R
Visualising Spatial Data
Spatial Data Import and Export
Further Methods for Handling Spatial Data
Classes for spatio
temporal Data
Spatial Point Pattern Analysis
Interpolation and Geostatistics
Modelling Areal Data
Disease Mapping
ISBN:9781461476184
Series:e-books
Series:SpringerLink (Online service)
Series:Use R! : v10
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Cartography
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Call number:SPRINGER-2013-9781461461142:ONLINE Show nearby items on shelf
Title:Sequential Experimentation in Clinical Trials [electronic resource] : Design and Analysis
Author(s): Jay Bartroff
Tze Leung Lai
Mei-Chiung Shih
Date:2013
Publisher:New York, NY : Springer New York : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:This book presents an integrated methodology for sequential experimentation in clinical trials. The methodology allows sequential learning during the course of a trial to improve the efficiency of the trial design, which oftenlacks adequate informati on at the planning stage. Adaptation via sequential learning of unknown parameters is a central idea not only in adaptive designs of confirmatory clinical trials but also in the theory of optimal nonlinearexperimental design, which the book covers as intr oductory material. Other introductory topics for which the book provides preparatory background include sequential testing theory, dynamic programming and stochastic optimization,survival analysis and resampling methods. In this way, the book gives a self -contained and thorough treatment of group sequential and adaptive designs, time-sequential trials with failure-time endpoints, and statistical inference atthe conclusion of these trials. The book can be used for graduate courses in sequential analysis, c linical trials, and biostatistics, and also for short courses on clinical trials at professional meetings. Each chapter ends withsupplements for the reader to explore related concepts and methods, and problems which can be used for exercises in graduate c ourses. Jay Bartroff is Associate Professor of Mathematics at the University of Southern California where heis a member of the Laboratory of Applied Pharmacokinetics at the USC Keck School of Medicine. He is a leading expert on group sequential and multis tage adaptive statistical procedures and their applications to clinical trial designs,and he is a sought-after consultant in academia and industry. Tze Leung Lai is Professor of Statistics, and by courtesy, of Health Research and Policy and of the Institu te of Computational and Mathematical Engineering at StanfordUniversity, where he is the Director of the Financial and Risk Modeling Institute and Co-director of the Biostatistics Core at the Stanford Ca
Note:Springer eBooks
Contents:Introduction
Nonlinear Regression, Experimental Design, and Phase I Clinical Trials
Sequential Testing Theory and Stochastic Optimization over Time
Group Sequential Design of Phase II and III Trials
Sequential Methods for Vaccine Safety Evaluation and Surveillance in Public Health
Time
Sequential Design of Clinical Trials with Failure
Time Endpoints
Confidence Intervals and p
Values
Adaptive Design of Confirmatory Trials
References
ISBN:9781461461142
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Series in Statistics, 0172-7397 : v298
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Mathematical statistics
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Call number:SPRINGER-2013-9781461455868:ONLINE Show nearby items on shelf
Title:Epidemiologic Studies in Cancer Prevention and Screening [electronic resource]
Author(s): Anthony B Miller
Date:2013
Publisher:New York, NY : Springer New York : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Epidemiologic Studies in Cancer Prevention and Screening is the first comprehensive overview of the evidence base for both cancer prevention and screening. This book is directed to the many professionals in government, academia,public health and heal th care who need up to date information on the potential for reducing the impact of cancer, including physicians, nurses, epidemiologists, and research scientists. The main aim of the book is to provide arealistic appraisal of the evidence for both cancer prevention and cancer screening. In addition, the book provides an accounting of the extent programs based on available knowledge have impacted populations. It does this through: 1.Presentation of a rigorous and realistic evaluation of the evidence for p opulation-based interventions in prevention of and screening for cancer, with particular relevance to those believed to be applicable now, or on the cusp ofapplication 2. Evaluation of the relative contributions of prevention and screening 3. Discussion o f how, within the health systems with which the authors are familiar, prevention and screening for cancer can be enhanced. Overview ofthe evidence base for cancer prevention and screening, as demonstrated in Epidemiologic Studies in Cancer Prevention and Screening, is critically important given current debates within the scientific community. Of the five componentsof cancer control, prevention, early detection (including screening) treatment, rehabilitation and palliative care, prevention is regarded as t he most important. Yet the knowledge available to prevent many cancers is incomplete, andeven if we know the main causal factors for a cancer, we often lack the understanding to put this knowledge into effect. Further, with the long natural history of mos t cancers, it could take many years to make an appreciable impactupon the incidence of the cancer. Because of these facts, many have come to believe that screening has the most potential for reduction o
Note:Springer eBooks
Contents:Health promotion in cancer prevention
Preventing cancer by ending tobacco use
Prevention of occupationally
induced cancer
The prospects for successful HPV vaccination for cervix and other cancers
Prevention of cancers due to infection
Applying physical activity in cancer prevention
Cancer prevention in the United States
The role of nutrition in cancer prevention
Chemoprevention of cancer: from nutritional epidemiology to clinical trials
The role of hormonal factors in cancer prevention
Controlling environmental causes of cancer
A historical moment: cancer preve
ISBN:9781461455868
Series:e-books
Series:SpringerLink (Online service)
Series:Statistics for Biology and Health, 1431-8776 : v79
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics
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Call number:SPRINGER-2013-9781461452454:ONLINE Show nearby items on shelf
Title:Proceedings of the Fourth Seattle Symposium in Biostatistics: Clinical Trials [electronic resource]
Author(s): Thomas R Fleming
Bruce S Weir
Date:2013
Publisher:New York, NY : Springer New York : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:This volume contains a selection of chapters based on papers presented at the Fourth Seattle Symposium on Biostatistics: Clinical Trials. These biostatistical symposiums, which unite leading researchers every five years,represent important developmen ts in field. The Fourth Seattle Symposium was held in 2010 to celebrate the 40th anniversary of the University of Washington School of Public Health and Community Medicine. The Symposium featured keynotelectures by Robert ONeill, Ross Prentice and Robert Temple, as well as invited talks by Jesse Berlin, Christy Chuang-Stein, David DeMets, Bill DuMouchel, Susan Ellenberg, Thomas Fleming, Laurence Freedman, Margaret Pepe, Steve Self,Richard Simon, Bruce Weir, John Whittaker and Janet Wittes. Invited panelis ts included Jesse Berlin, Bruce Binkowitz, Christy Chuang-Stein, Bill DuMouchel, Susan Ellenberg, Thomas Fleming, Henry Fuchs, Dominic Labriola, RobertONeill, Robert Temple and Janet Wittes. The thoroughly peer-reviewed papers and material from short cour ses that are showcased in this volume represent the theme of the symposium, clinical trials. These papers encompass recentmethodological advances on several important topics, summaries of the state of the art of methodology in key areas of clinical trials , as well as innovative applications of the existing theory and methods. This volume will be avaluable reference for researchers and practitioners in the field of clinical trials
Note:Springer eBooks
ISBN:9781461452454
Series:e-books
Series:SpringerLink (Online service)
Series:Lecture Notes in Statistics, 0930-0325 : v1205
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics
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Call number:SPRINGER-2013-9781461448549:ONLINE Show nearby items on shelf
Title:SAS for Epidemiologists [electronic resource] : Applications and Methods
Author(s): Charles DiMaggio
Date:2013
Publisher:New York, NY : Springer New York : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:This comprehensive text covers the use of SAS for epidemiology and public health research. Developed with students in mind and from their feedback, the text addresses this material in a straightforward manner with a multitude ofexamples. It is direct ly applicable to students and researchers in the fields of public health, biostatistics and epidemiology. Through a hands on approach to the use of SAS for a broad number of epidemiologic analyses, readerslearn techniques for data entry and cleaning, cate gorical analysis, ANOVA, and linear regression and much more. Exercises utilizing real-world data sets are featured throughout the book. SAS screen shots demonstrate the steps forsuccessful programming. SAS (Statistical Analysis System) is an integrated s ystem of software products provided by the SAS institute, which is headquartered in California. It provides programmers and statisticians the ability to engagein many sophisticated statistical analyses and data retrieval and mining exercises. SAS is widel y used in the fields of epidemiology and public healthresearch, predominately due to its ability to reliably analyze very largeadministrative data sets, as well as more commonly encountered clinical trial and observational research data.
Note:Springer eBooks
Contents:Introduction
The SAS Environment
Working with SAS Data
Preliminary Procedures
Manipulating Data
Descriptive Statistics
Histograms and Plots
Categorical Data Analysis I and II
Cleaning and Assessing Continuous Data using MEANS
ANOVA
Correlation
Linear Regression
Regression Diagnostics
Solutions
ISBN:9781461448549
Series:e-books
Series:SpringerLink (Online service)
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics
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Call number:SPRINGER-2013-9781461439004:ONLINE Show nearby items on shelf
Title:Linear Mixed-Effects Models Using R [electronic resource] : A Step-by-Step Approach
Author(s): Andrzej Gaecki
Tomasz Burzykowski
Date:2013
Publisher:New York, NY : Springer New York : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Linear mixed-effects models (LMMs) are an important class of statistical models that can be used to analyze correlated data. Such data are encountered in a variety of fields including biostatistics, public health, psychometrics,educational measuremen t, and sociology. This book aims to support a wide range of uses for the models by applied researchers in those and other fields by providing state-of-the-art descriptions of the implementation of LMMs in R. Tohelp readers to get familiar with the feature s of the models and the details of carrying them out in R, the book includes a review of the most important theoretical concepts of the models. The presentation connects theory, software andapplications. It is built up incrementally, starting with a summa ry of the concepts underlying simpler classes of linear models like the classical regression model, and carrying them forward to LMMs. A similar step-by-step approach isused to describe the R tools for LMMs. All the classes of linear models presented in t he book are illustrated using real-life data. The book also introduces several novel R tools for LMMs, including new class of variance-covariancestructure for random-effects, methods for influence diagnostics and for power calculations. They are included into an R package that should assist the readers in applying these and other methods presented in this text. Andrzej Gaeckiis a Research Professor in the Division of Geriatric Medicine, Department of Internal Medicine, and Institute of Gerontology at the University of Michigan Medical School, and is Research Scientist in the Department of Biostatistics atthe University of Michigan School of Public Health. He earned his M.Sc. in applied mathematics (1977) from the Technical University of Warsaw, Poland, an d an M.D. (1981) from the Medical University of Warsaw. In 1985 he earned a Ph.D.in epidemiology from the Institute of Mother and Child Care in Warsaw (Poland). He is a member of the Editorial Board o
Note:Springer eBooks
Contents:Introduction
Linear Models for Independent Observations
Linear Fixed
effects Models for Correlated Data
Linear Mixed
effects Models
ISBN:9781461439004
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Texts in Statistics, 1431-875X
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Mathematical statistics
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Call number:SPRINGER-2013-9781461436492:ONLINE Show nearby items on shelf
Title:Strength in Numbers: The Rising of Academic Statistics Departments in the U. S. [electronic resource]
Author(s): Alan Agresti
Xiao-Li Meng
Date:2013
Publisher:New York, NY : Springer New York : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
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Note:Statistical science as organized in formal academic departments is relatively new. With a few exceptions, most Statistics and Biostatistics departments have been created within the past 60 years. This book consists of a setof memoirs, one for each de partment in the U.S. created by the mid-1960s. The memoirs describe key aspects of the departments history -- its founding, its growth, key people in its development, success stories (such as majorresearch accomplishments) and the occasional failure story , PhD graduates who have had a significant impact, its impact on statistical education, and a summary of where the department stands today and its vision for the future. Readhere all about how departments such as at Berkeley, Chicago, Harvard, and Stanfor d started and how they got to where they are today. The book should also be of interest to scholars in the field of disciplinary history
Note:Springer eBooks
Contents:Statistics as an Academic Discipline
Carnegie
Mellon
Columbia University
Cornell University
Florida State University
George Washington University
Harvard University
Harvard University
Iowa State University
Johns Hopkins University
Kansas State University
Michigan State University
North Carolina State
Oregon State University
Penn State University
Princeton University
Purdue University
Rutgers University
Southern Methodist University
Stanford University
SUNY at Buffalo
Texas A&M
University of California
University of Chicago
ISBN:9781461436492
Series:e-books
Series:SpringerLink (Online service)
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Science History , Public health , Computer science , Education, Higher , Social sciences
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Call number:SPRINGER-2012-9781461412052:ONLINE Show nearby items on shelf
Title:Epidemiology [electronic resource] : Key to Prevention
Author(s): Klaus Krickeberg
Van Trong Pham
Thi My Hanh Pham
Date:2012
Publisher:New York, NY : Springer New York : Imprint: Springer
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:This book is meant for adoption in first courses on epidemiology in Medical Schools and Faculties of Public Health in developing and transition countries and in workshops in these countries, taught for example by members ofinternational organizations . It is also suitable for parallel or second reading within curricula in developed countries and for teaching epidemiology in a Masters programme on International Health. The book will enable anylecturer to compose his or her introductory courses on epide miology by selecting the material deemed appropriate. It will provide a solid foundation for more advanced teaching. The intended readership consists in the first place ofgeneral medical students students following the programme Preventive Physician that runs parallel to general medical studies in some countries students starting to specialize in Public Health and lecturers in epidemiology. Thebook can also serve well as an introduction into epidemiology for anybody else interested in this field, for exam ple staff of health institutions. Examples and practical work are taken from the present situation of health in Vietnam,which can easily be adapted to any other developing or transition country
Note:Springer eBooks
Contents:The idea of epidemiology
Uses and applications of epidemiology
Some case studies and situation analyses
Infectious diseases: descriptive epidemiology, transmissions, surveillance, control
Infectious diseases: modelling, immunity
Diarrhoea and cholera
Tuberculosis and malaria
Dengue fever
Viral hepatitis
HIV/AIDS
The origin of information: registers and health information systems
The origin of information: sampling
Descriptive data analysis and statistics
The normal law and applications
Basic concepts of epidemiology
Cross sectional studies
Cohort
ISBN:9781461412052
Series:e-books
Series:SpringerLink (Online service)
Series:Statistics for Biology and Health, 1431-8776
Series:Mathematics and Statistics (Springer-11649)
Keywords: Medicine , Epidemiology , Statistical methods , Statistics
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Call number:SPRINGER-2012-9781441966469:ONLINE Show nearby items on shelf
Title:Survival Analysis [electronic resource] : A Self-Learning Text, Third Edition
Author(s): David G Kleinbaum
Mitchel Klein
Date:2012
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:This greatly expanded third edition of Survival Analysis- A Self-learning Text provides a highly readable description of state-of-the-art methods of analysis of survival/event-history data. This text is suitable for researchersand statisticians worki ng in the medical and other life sciences as well as statisticians in academia who teach introductory and second-level courses on survival analysis. The third edition continues to use the unique lecture-bookformat of the firsttwo editions with one new cha pter, additionalsections and clarifications to several chapters, and a revised computer appendix. The Computer Appendix, with step-by-stepinstructions for using the computerpackages STATA, SAS, and SPSS, is expandedtoinclude the software package R. David Kleinbaum is Professor of Epidemiology at the Rollins School of Public Health at Emory University, Atlanta, Georgia. Dr. Kleinbaum is internationallyknown for innovative textbooks and teaching on epidemiological methods, multiple linear regression, logist ic regression, and survival analysis. He has provided extensive worldwide short-course training in over 150 short courses onstatistical and epidemiological methods. He is also the author of ActivEpi (2002), an interactive computer-based instructional text on fundamentals of epidemiology, which has been used in a variety of educational environments includingdistance learning. Mitchel Klein is Research Assistant Professor with a joint appointment in the Department of Environmental and Occupational Health (E OH) and the Department of Epidemiology, also at the Rollins School of Public Healthat Emory University. Dr. Klein is also co-author with Dr. Kleinbaum of the second edition of Logistic Regression- A Self-Learning Text (2002). He has regularly taught epide miologic methods courses at Emory to graduate students inpublic health and in clinical medicine. He is responsible for the epidemiologic methods training of physicians enrolled in Emorys
Note:Springer eBooks
Contents:Introduction to Survival Analysis
Kaplan
Meier Survival Curves and the Log
Rank Test
The Cox Proportional Hazards Model and Its Characteristics
Evaluating the Proportional Hazards Assumption
The Stratified Cox Procedure
Extension of the Cox Proportional Hazards Model for Time
Dependent Variables
Parametric Survival Models
Recurrent Events Survival Analysis
Competing Risks Survival Analysis
ISBN:9781441966469
Series:e-books
Series:SpringerLink (Online service)
Series:Statistics for Biology and Health, 1431-8776
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Epidemiology
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Call number:SPRINGER-2012-9781441907455:ONLINE Show nearby items on shelf
Title:Sustainable Environmental Design in Architecture [electronic resource] : Impacts on Health
Author(s): Stamatina Th Rassia
Panos M Pardalos
Date:2012
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
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Note:The chapters in this book, written by international experts from different fields of architecture and engineering, are devoted to recent interdisciplinary works in a variety of subjects related to sustainable architecture andengineering, environmenta l modeling, behavioral science and public health. The invited contributions focus on new ideas, concepts and research work with multidisciplinary applications. Special features of this volume include indoorand urban design impacts on human comfort, model ing and assessment of multi-scale design dynamics, as well as new results from diverse areas of research spanning from architecture and engineering to neuroscience and public health. Sustainable Environmental Design in Architecture is intended for graduat e students and researchers of architecture, engineering, neuroscience, public health, social and computational sciences, architectural modeling and relatedfields
Note:Springer eBooks
Contents:1. Sustainability and Neuroscience (J.P. Eberhard)
2. Behavioral Science Perspectives on Designing the Environment to Promote Child Health (M.E. Sharff, E. Gerfen, K.P. Tercyak)
3. Form Follows Function: Bridging Neuroscience and Architecture (E.A. Edelstein, E. Macagno)
4. Active Transport, Building Environment and Human Health (T. Sugiyama, M. Neuhaus, N. Owen)
5. Environmental Control and the Creation of Wellbeing (S. Manchanda, K. Steemers)
6 Design of Healthy, Comfortable Energy Efficient Buildings (C.A. Roulet, P. Bluysssen, B. Muller, E. de Oliveira Fernandes)
7. Envir
ISBN:9781441907455
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Optimization and Its Applications, 1931-6828 : v56
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Engineering design , Civil engineering , Environmental Medicine , Sustainable development
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Call number:SPRINGER-2011-9781441998422:ONLINE Show nearby items on shelf
Title:Modern Issues and Methods in Biostatistics [electronic resource]
Author(s): Mark Chang
Date:2011
Publisher:New York, NY : Springer New York
Size:1 online resource
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Note:Classic biostatistics, a branch of statistical science, has as its main focus the applications of statistics in public health, the life sciences, and the pharmaceutical industry. Modern biostatistics, beyond just a simpleapplication of statistics, is a confluence of statistics and knowledge of multiple intertwined fields. The application demands, the advancements in computer technology, and the rapid growth of life science data (e.g., genomics data)have promoted the formation of modern biostatistics. There are at least three characteristics of modern biostatistics: (1) in-depth engagement in the application fields that require penetration of knowledge across several fields, (2)high-level complexity of data because they are longitudinal, incomplete, o r latent because they are heterogeneous due to a mixture of data or experiment types, because of high-dimensionality, which may make meaningful reductionimpossible, or because of extremely small or large size and (3) dynamics, the speed of development in methodology and analyses, has to match the fast growth of data with a constantly changing face. This book is written forresearchers, biostatisticians/statisticians, and scientists who are interested in quantitative analyses. The goal is to introduce moder n methods in biostatistics and help researchers and students quickly grasp key concepts and methods.Many methods can solve the same problem and many problems can be solved by the same method, which becomes apparent when those topics are discussed inthis s ingle volume
Note:Springer eBooks
Contents:Multiple
Hypothesis Testing Strategy
Pharmaceutical Decision and Game Theory
Noninferiority Trial Design
Adaptive Trial Design
Missing Data Imputation and Analysis
Multivariate and Multistage Survival Data Modeling
Meta
analysis
Data Mining and Signal Detection
Monte Carlo Simulation
Bayesian Methods and Applications
ISBN:9781441998422
Series:e-books
Series:SpringerLink (Online service)
Series:Statistics for Biology and Health, 1431-8776
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Data mining , Mathematics , Engineering
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Call number:SPRINGER-2011-9781441973382:ONLINE Show nearby items on shelf
Title:The Fundamentals of Modern Statistical Genetics [electronic resource]
Author(s): Nan M Laird
Date:2011
Publisher:New York, NY : Springer New York
Size:1 online resource
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Note:This book covers the statistical models and methods that are used to understand human genetics, following the historical and recent developments of human genetics. Starting with Mendels first experiments to genome-wideassociation studies, the book de scribes how genetic information can be incorporated into statistical models to discover disease genes. All commonly used approaches in statistical genetics (e.g. aggregation analysis, segregation,linkage analysis, etc), are used, but the focus of the book is modern approaches to association analysis. Numerous examples illustrate key points throughout the text, both of Mendelian and complex genetic disorders. The intendedaudience is statisticians, biostatisticians, epidemiologists and quantitatively- orien ted geneticists and health scientists wanting to learn about statistical methods for genetic analysis, whether to better analyze genetic data, or topursue research in methodology. A background in intermediate level statistical methods is required. The aut hors include few mathematical derivations, and the exercises provide problems for students with a broad range of skill levels.No background in genetics is assumed. Dr. Laird is a Professor of Biostatistics in the Biostatistics Department at the Harvard Sc hool of Public Health. Dr. Laird has contributed to methodology in many different fields, includingmissing data, EM-algorithm, meta-analysis, statistical genetics, and has coauthored a book with Garrett Fitzmaurice and James Ware on Applied Longitudinal A nalysis. She is the recipient of many awards and prizes, including Fellow ofthe American Statistical Association, the American Association for the Advancement of Science, the Florence Nightingale Award, and the Janet Norwood Award. Dr. Lange is an Associa te Professor in the Biostatistics Department at theHarvard School of Public Health. After his PhD in Statistics at the University of Reading (UK), he has worked extensively in the field of statistica
Note:Springer eBooks
Contents:Introduction to statistical genetics and background in molecular genetics
Principles of inheritance: mendel's laws and genetic models
Some basic concepts from population genetics
Aggregation, heritability and segregation analysis: modeling genetic inheritance without genetic data
The general concepts of gene mapping: Linkage, association, linkage disequilibrium and marker maps
Basic concepts of linkage analysis
The basics of genetic association analysis
Population substructure in association studies
Association analysis in family designs
Advanced topics
Genome wid
ISBN:9781441973382
Series:e-books
Series:SpringerLink (Online service)
Series:Statistics for Biology and Health, 1431-8776
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Human genetics , Epidemiology , Biometrics , Statistical methods
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Call number:SPRINGER-2010-9781441968241:ONLINE Show nearby items on shelf
Title:Recursive Partitioning and Applications [electronic resource]
Author(s): Heping Zhang
Burton H Singer
Date:2010
Edition:Second
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
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Note:The routes to many important outcomes including diseases and ultimately death as well as financial credit consist of multiple complex pathways containing interrelated events and conditions. We have historically lacked effectivemethodologies for ident ifying these pathways and their non-linear and interacting features. This book focuses on recursive partitioning strategies as a response to the challenge of pathway characterization. A highlight of the secondedition is the many worked examples, most of t hem from epidemiology, bioinformatics, molecular genetics, physiology, social demography, banking, and marketing. The statistical issues, conceptual and computational, are not only treatedin detail in the context of important scientific questions, but als o an array of substantively-driven judgments are explicitly integrated in the presentation of examples. Going considerably beyond the standard treatments of recursivepartitioning that focus on pathway representations via single trees, this second edition has entirely new material devoted to forests from predictive and interpretive perspectives. For contexts where identification of factorscontributing to outcomes is a central issue, both random and deterministic forest generation methods are introduced via examples in genetics and epidemiology. The trees in deterministic forests are reproducible and more easilyinterpretable than the components of random forests. Also new in the second edition is an extensive treatment of survival forests and post-market ev aluation of treatment effectiveness. Heping Zhang is Professor of Public Health,Statistics, and Child Study, and director of the Collaborative Center for Statistics in Science, at Yale University. He is a Fellow of the American Statistical Association and the Institute of Mathematical Statistics, a MyrtoLefkopoulou Distinguished Lecturer Awarded by Harvard School of Public Health, and a Medallion lecturer selected by the Institute of Mathematical Statis
Note:Springer eBooks
Contents:Introduction
A Practical Guide to Tree Construction
Logistic Regression
Classification Trees for a Binary Response
Examples Using Tree
Based Analysis
Random and Deterministic Forests
Analysis of Censored Data: Examples
Analysis of Censored Data: Concepts and Classical Methods
Analysis of Censored Data: Survival Trees and Random Forests
Regression Trees and Adaptive Splines for a Continuous Response
Analysis of Longitudinal Data
Analysis of Multiple Discrete Responses
ISBN:9781441968241
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Series in Statistics, 0172-7397 : v0
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics
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Call number:SPRINGER-2010-9781441917423:ONLINE Show nearby items on shelf
Title:Logistic Regression [electronic resource] : A Self-Learning Text
Author(s): David G Kleinbaum
Mitchel Klein
Date:2010
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:This very popular textbook is now in its third edition. Whether students or working professionals, readers appreciate its unique lecture book format. They often say the book reads like they are listening to an outstandinglecturer. This edition includ es three new chapters, an updated computer appendix, and an expanded section about modeling guidelines that consider causal diagrams. Like previous editions, this textbook provides a highly readabledescription of fundamental and more advanced concepts and methods of logistic regression. It is suitable for researchers and statisticians in medical and other life sciences as well as academicians teaching second-level regressionmethods courses. The new chapters are: Additional Modeling Strategy Issues, inclu ding strategy with several exposures, screening variables, collinearity, influential observations and multiple-testing Assessing Goodness to Fitfor Logistic Regression Assessing Discriminatory Performance of a Binary Logistic Model: ROC Curves The Compu ter Appendix provides step-by-step instructions for using STATA (version 10.0), SAS (version 9.2), and SPSS (version 16)for procedures described in the main text. David Kleinbaum is Professor of Epidemiology at Emory University Rollins School of Public He alth in Atlanta, Georgia. Dr. Kleinbaum is internationally known for his innovative textbooks andteaching on epidemiological methods, multiple linear regression, logistic regression, and survival analysis. He has taught more than 200 courses worldwide. Th e recipient of numerous teaching awards, he received the first Association ofSchools of Public Health Pfizer Award for Distinguished Career Teaching in 2005. Mitchel Klein is Research Assistant Professor with a joint appointment in the Environmental and O ccupational Health Department and the EpidemiologyDepartment at Emory University Rollins School of Public Health. He has successfully designed and taught epidemiologic methods physicians at E
Note:Springer eBooks
Contents:Introduction to logistic regression
Important special cases of the logistic model
Computing the odds ratio in logistic regression
Maximum likelihood techniques: An overview
Statistical inferences using maximum likelihood techniques
modeling strategy guidelines
Modeling strategy for assessing interaction and confounding
Additional modeling strategy issues
Assessing Goodness of Fit for logistic regression
Assessing discriminatory performance of a binary logistic regression model: ROC curves
Analysis of matched data using logistic regression
Polytomous logistic re
ISBN:9781441917423
Series:e-books
Series:SpringerLink (Online service)
Series:Statistics for Biology and Health, 1431-8776
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Epidemiology
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Call number:SPRINGER-2010-9781441915863:ONLINE Show nearby items on shelf
Title:Fundamentals of Clinical Trials [electronic resource]
Author(s): Lawrence M Friedman
Curt D Furberg
David L DeMets
Date:2010
Edition:Fourth
Publisher:New York, NY : Springer New York : Imprint: Springer
Size:1 online resource
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Note:This is the fourth edition of a very successful textbook on clinical trials methodology, written by three recognized experts who have long and extensive experience in all areas of clinical trials. Most chapters have been revisedconsiderably from the third edition. A chapter on ethics has been added and topics such as noninferiority and adaptive designs now receive considerable discussion. There is much new material on adverse events, adherence, datamonitoring, and issues in analysis. This book is int ended for the clinical researcher who is interested in designing a clinical trial and developing a protocol. It is also of value to researchers and practitioners who must criticallyevaluate the literature of published clinical trials and assess the merits of each trial and the implications for the care and treatment of patients. The authors use numerous examples of published clinical trials from a variety ofmedical disciplines to illustrate the fundamentals. The text is organized sequentially from definin g the question to trial closeout. One chapter is devoted to each of the critical areas to aid the clinical trial researcher. These areasinclude pre-specifying the scientific questions to be tested and appropriate outcome measures, determining the organiza tional structure, estimating an adequate sample size, specifying the randomization procedure, implementing theintervention and visit schedules for participant evaluation, establishing an interim data and safety monitoring plan, detailing the final analysi s plan, and reporting the trial results according to the pre-specified objectives.Although a basic introductory statistics course is helpful in maximizing the benefit of this book, a researcher or practitioner with limited statistical background would sti ll find most if not all the chapters understandable andhelpful. While the technical material has been kept to a minimum, the statistician may still find the principles and fundamentals presented in this
Note:Springer eBooks
Contents:Introduction to clinical trials
Ethical issues
What is the question?
Study population
Basic study design
The randomization process
Blindness
Sample size
Baseline assessment
Recruitment of study participants
Data collection and quality control
Assessing and reporting adverse effects
Assessment of health
related quality of life
Participant adherence
Survival analysis
Monitoring response variables
Issues in data analysis
Closeout
Reporting and interpreting of results
Multicenter trials
ISBN:9781441915863
Series:e-books
Series:SpringerLink (Online service)
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Oncology , Public health , Epidemiology
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Call number:SPRINGER-2010-9781441915726:ONLINE Show nearby items on shelf
Title:Statistical Methods for Disease Clustering [electronic resource]
Author(s): Toshiro Tango
Date:2010
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:The development of powerful computing environment and the geographical information system (GIS) in recent decades has thrust the analysis of geo-referenced disease incidence data into the mainstream of spatial epidemiology. Thisbook offers a modern p erspective on statistical methods for detecting disease clustering, an indispensable procedure to find a statistical evidence on aetiology of the disease under study. With increasing public health concerns aboutenvironmental risks, the need for sophistica ted methods for analyzing spatial health events is immediate. Furthermore, the research area of statistical methods for disease clustering now attracts a wide audience due to the perceivedneed to implement wide-ranging monitoring systems to detect possibl e health-related events such as the occurrence of the severe acute respiratory syndrome (SARS), pandemic influenza and bioterrorism As an invaluable resource for a widerange of audience including public health researchers, epidemiologists and biostatistia ns, this book features: A concise introduction to basic concepts of disease clustering/clusters A historical overview of methods for diseaseclustering A detailed treatment of selected methods useful for practical investigation of disease clustering Analys is and illustration of methods for a variety of real data sets Toshiro Tango, Ph.D., is the Director of Department ofTechnology Assessment and Biostatistics of National Institute of Public Health, Japan. He has published a number of methodological and app lied articles on various aspects of biostatistics. He is Past President of the Japanese Region ofthe International Biometric Society. He has served as Associate Editor for several journals including Statistics in Medicine and Biometrics
Note:Springer eBooks
Contents:Introduction
Clustering and clusters
Disease mapping: Visualization of spatial clustering
Tests for temporal clustering
General tests for spatial clustering: Regional count data
General tests for spatial clustering: Case
control point data
Tests for space
time clustering
Focused tests for spatial clustering
Space
time scan statistics
ISBN:9781441915726
Series:e-books
Series:SpringerLink (Online service)
Series:Statistics for Biology and Health, 1431-8776
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Oncology , Epidemiology , Biometrics , Statistical methods
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Call number:SPRINGER-2010-9780387938356:ONLINE Show nearby items on shelf
Title:Modern Infectious Disease Epidemiology [electronic resource] : Concepts, Methods, Mathematical Models, and Public Health
Author(s): Alexander Krmer
Mirjam Kretzschmar
Klaus Krickeberg
Date:2010
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Hardly a day goes by without news headlines concerning infectious disease threats. Currently the spectre of a pandemic of influenza A|H1N1 is raising its head, and heated debates are taking place about the pros and cons ofvaccinating young girls agai nst human papilloma virus. For an evidence-based and responsible communication of infectious disease topics to avoid misunderstandings and overreaction of the public, we need solid scientific knowledge andan understanding of all aspects of infectious dise ases and their control. The aim of our book is to present the reader with the general picture and the main ideas of the subject. The book introduces the reader to methodological aspectsof epidemiology that are specific for infectious diseases and provides insight into the epidemiology of some classes of infectious diseases characterized by their main modes of transmission. This choice of topics bridges the gapbetween scientific research on the clinical, biological, mathematical, social and economic aspect s of infectious diseases and their applications in public health. The book will help the reader to understand the impact of infectiousdiseases on modern society and the instruments that policy makers have at their disposal to deal with these challenges. I t is written for students of the health sciences, both of curative medicine and public health, and for expertsthat are active in these and related domains, and it may be of interest for the educated layman since the technical level is kept relatively low. The authors are internationally renowned experts in the field of infectious diseaseepidemiology. The editors come from different scientific backgrounds but have been devoted to research in infectious disease epidemiology for many years. Alexander Krmer i s an internist and epidemiologist who co-founded the firstSchool of Public Health in the German-speaking region of Europe at the University of Bielefeld. Mirjam Kretzschmar is a mathematician an
Note:Springer eBooks
Contents:I Challenges
The Global Burden of Infectious Diseases
Global Challenges of Infectious Disease Epidemiology
EmergingEmerging infectious diseases and Re
emerging Infectious Diseases
Infectious Disease Control Policies and the Role of Governmental and Intergovernmental Organisations
II General concepts and methods
Principles of Infectious Disease Epidemiology
Social Risk Factors
Molecular Typing and Clustering Analysis as a Tool for Epidemiology of Infectious Diseases
Epidemiologic Surveillance
Outbreak Investigations
Geographic Information Systems
Methods and
ISBN:9780387938356
Series:e-books
Series:SpringerLink (Online service)
Series:Statistics for Biology and Health, 1431-8776
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Medicine , Emerging infectious diseases , Cartography , Statistical methods
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Call number:SPRINGER-2010-9780387686363:ONLINE Show nearby items on shelf
Title:Design and Analysis of Vaccine Studies [electronic resource]
Author(s): M. Elizabeth Halloran
Jr. Longini Ira M
Claudio J Struchiner
Date:2010
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
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Note:Widespread immunization has many different kinds of effects in individuals and populations, including in the unvaccinated individuals. The challenge is in understanding and estimating all of these effects. This book presents aunified conceptual frame work of the different effects of vaccination at the individual and at the population level. The book covers many different vaccine effects, including vaccine efficacy for susceptibility, for disease, forpost-infection outcomes, and for infectiousness. The book includes methods for evaluating indirect, total and overall effects of vaccination programs in populations. Topics include household studies, evaluating correlates of immuneprotection, and applications of casual inference. Material on concepts of in fectious disease epidemiology, transmission models, casual inference, and vaccines provides background for the reader. This is the first book to presentvaccine evaluation in this comprehensive conceptual framework. This book is intended for colleagues and students in statistics, biostatistics, epidemiology, and infectious diseases. Most essential concepts are described in simplelanguage accessible to epidemiologists, followed by technical material accessible to statisticians. M. Elizabeth Halloran and Ira Longini are professors of biostatistics at the University of Washington and the Fred Hutchinson CancerResearch Center in Seattle. Claudio Struchiner is professor of epidemiology and biostatistics at the Brazilian School of Public Health of the Oswaldo Cr uz Foundation in Rio de Janeiro. The authors are prominent researchers in the area.Halloran and Struchiner developed the study designs for dependent happenings to delineate indirect, total, and overall effects. Halloran has made contributions at the inter face of epidemiological methods, causal inference, andtransmission dynamics. Longini works in the area of stochastic processes applied to epidemiological infectious disease problems, specializing in the
Note:Springer eBooks
Contents:Introduction and examples
Overview of vaccine effects and study designs
Immunology and early phase trials
binomial and stochastic transmission models
R0 and deterministic models
Evaluating protective effects of vaccination
Modes of action and time
varying VES
Further Evaluation of Protective Effects
Vaccine effects on post
infection outcomes
House
hold based studies
Analysis of households in communities
Analysis of independent households
Assessing Indirect, total and overall effects
Randomization and baseline transmission
Surrogates of protection
ISBN:9780387686363
Series:e-books
Series:SpringerLink (Online service)
Series:Statistics for Biology and Health, 1431-8776
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Emerging infectious diseases
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Call number:SPRINGER-2009-9783642032059:ONLINE Show nearby items on shelf
Title:Downward Causation and the Neurobiology of Free Will [electronic resource]
Author(s): Nancey Murphy
George F. R Ellis
Timothy OConnor
Date:2009
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:How is free will possible in the light of the physical and chemical underpinnings of brain activity and recent neurobiological experiments? How can the emergence of complexity in hierarchical systems such as the brain, based atthe lower levels in phy sical interactions, lead to something like genuine free will? The nature of our understanding of free will in the light of present-day neuroscience is becoming increasingly important because of remarkablediscoveries on the topic being made by neuroscienti sts at the present time, on the one hand, and its crucial importance for the way we view ourselves as human beings, on the other. A key tool in understanding how free will may arise inthis context is the idea of downward causation in complex systems, happ ening coterminously with bottom up causation, to form an integral whole. Top-down causation is usually neglected, and is therefore emphasized in the other part ofthe books title. The concept is explored in depth, as are the ethical and legal implications of our understanding of free will. This book arises out of a workshop held in California in April of 2007, which was chaired by Dr.Christof Koch. It was unusual in terms of the breadth of people involved: they included physicists, neuroscientists, psychia trists, philosophers, and theologians. This enabled the meeting, and hence the resulting book, to attain arather broader perspective on the issue than is often attained at academic symposia. The book includes contributions by Sarah-Jayne Blakemore, George F. R. Ellis , Christopher D. Frith, Mark Hallett, David Hodgson, Owen D. Jones,Alicia Juarrero, J. A. Scott Kelso, Christof Koch, Hans Kng, Hakwan C. Lau, Dean Mobbs, Nancey Murphy, William Newsome, Timothy OConnor, Sean A.. Spence, and Evan Thompson
Note:Springer eBooks
Contents:and Overview
and Overview
I: Physics, Emergence, and Complex Systems
Free Will, Physics, Biology, and the Brain
Human Freedom Emergence
Top
Down Causation and the Human Brain
Top
Down Causation and Autonomy in Complex Systems
Toward a Complementary Neuroscience: Metastable Coordination Dynamics of the Brain
II: Volition and Consciousness: Are They Illusions?
Physiology of Volition
How We Recognize Our Own Actions
Volition and the Function of Consciousness
III: Broader Understandings of Volition and Consciousness
Conscious Willing and the Emerging Sc
ISBN:9783642032059
Series:e-books
Series:SpringerLink (Online service)
Series:Understanding Complex Systems, 1860-0832
Series:Physics and Astronomy (Springer-11651)
Keywords: Neurosciences , Differentiable dynamical systems , Public health laws , Vibration
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Call number:SPRINGER-2009-9780387981352:ONLINE Show nearby items on shelf
Title:Principles and Theory for Data Mining and Machine Learning [electronic resource]
Author(s): Bertrand Clarke
Ernest Fokoue
Hao Helen Zhang
Date:2009
Publisher:New York, NY : Springer New York
Size:1 online resource
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Note:This book is a thorough introduction to the most important topics in data mining and machine learning. It begins with a detailed review of classical function estimation and proceeds with chapters on nonlinear regression,classification, and ensemble m ethods. The final chapters focus on clustering, dimension reduction, variable selection, and multiple comparisons. All these topics have undergone extraordinarily rapid development in recent years and thistreatment offers a modern perspective emphasizing the most recent contributions. The presentation of foundational results is detailed and includes many accessible proofs not readily available outside original sources. While theorientation is conceptual and theoretical, the main points are regularly reinf orced by computational comparisons. Intended primarily as a graduate level textbook for statistics, computer science, and electrical engineering students,this book assumes only a strong foundation in undergraduate statistics and mathematics, and facility with using R packages. The text has a wide variety of problems, many of an exploratory nature. There are numerous computed examples,complete with code, so that further computations can be carried out readily. The book also serves as a handbook for researc hers who want a conceptual overview of the central topics in data mining and machine learning. Bertrand Clarkeis a Professor of Statistics in the Department of Medicine, Department of Epidemiology and Public Health, and the Center for Computational Scienc es at the University of Miami. He has been on the Editorial Board of the Journal of theAmerican Statistical Association, the Journal of Statistical Planning and Inference, and Statistical Papers. He is co-winner, with Andrew Barron, of the 1990 Browder J. Thompson Prize from the Institute of Electrical and ElectronicEngineers. Ernest Fokoue is an Assistant Professor of Statistics at Kettering University. He has also taught at Ohio State University and b
Note:Springer eBooks
Contents:Variability, information, prediction
Kernel smoothing
Spline smoothing
New wave nonparametrics
Supervised learning: Partition methods
Alternative nonparametrics
Computational comparisons
Unsupervised learning: Clustering
Learning in high dimensions
Variable selection
Multiple testing
ISBN:9780387981352
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Series in Statistics, 0172-7397
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Computer science , Data mining , Optical pattern recognition , Bioinformatics , Mathematical statistics
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Call number:SPRINGER-2009-9780387879598:ONLINE Show nearby items on shelf
Title:Applying Quantitative Bias Analysis to Epidemiologic Data [electronic resource]
Author(s): Timothy L Lash
Matthew P Fox
Aliza K Fink
Date:2009
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:This text provides the first-ever compilation of bias analysis methods for use with epidemiologic data. It guides the reader through the planning stages of bias analysis, including the design of validation studies and thecollection of validity data f rom other sources. Three chapters present methods for corrections to address selection bias, uncontrolled confounding, and classification errors. Subsequent chapters extend these methods to multidimensionalbias analysis, probabilistic bias analysis, and m ultiple bias analysis. The text concludes with a chapter on presentation and interpretation of bias analysis results. Although techniques for bias analysis have been available fordecades, these methods are considered difficult to implement. This text not only gathers the methods into one cohesive and organized presentation, it also explains the methods in a consistent fashion and provides customizablespreadsheets to implement the solutions. By downloading the spreadsheets (available at links provided in t he text), readers can follow the examples in the text and then modify the spreadsheet to complete their own bias analyses.Readers without experience using quantitative bias analysis will be able to design, implement, and understand bias analyses that addr ess the major threats to the validity of epidemiologic research. More experienced analysts will valuethe compilation of bias analysis methods and links to software tools that facilitate their projects. Timothy L. Lash is an Associate Professor of Epidemio logy and Matthew P. Fox is an Assistant Professor in the Center for InternationalHealth and Development, both at the Boston University School of Public Health. Aliza K. Fink is a Project Manager at Macro International in Bethesda, Maryland. Together they have organized and presented many day-long workshops on themethods of quantitative bias analysis. In addition, they have collaborated on many papers that developed methods of quantitative bias analysis
Note:Springer eBooks
Contents:Introduction, objectives and an alternative
A guide to implementing quantitative bias analysis
Data sources for bias analysis
Selection bias
Unmeasured and unknown confounders
Misclassification
Multidimensional bias analysis
Probabilistic bias analysis
Multiple bias modeling
Presentation and inference
ISBN:9780387879598
Series:e-books
Series:SpringerLink (Online service)
Series:Statistics for Biology and Health, 1431-8776
Series:Mathematics and Statistics (Springer-11649)
Keywords: Medicine , Emerging infectious diseases , Epidemiology , Computer simulation , Statistics , Social sciences Methodology
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Call number:SPRINGER-2009-9780387781938:ONLINE Show nearby items on shelf
Title:Cancer Mortality and Morbidity Patterns in the U.S. Population [electronic resource] : An Interdisciplinary Approach
Author(s): K.G Manton
Igor Akushevich
Julia Kravchenko
Date:2009
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:This book is the first of its kind to describe interdisciplinary approaches to biomedical studies. It views analyses of biomedical data sets, such as cancer morbidity and mortality, from a different and richer than classicepidemiological perspective by using mathematical modeling methods, including ones providing insights into probable mechanisms of human carcinogenesis. The book will be useful for many specialists, e.g., epidemiologists, oncologists,medical researchers, biologists, public health and environmental specialists, and specialists in mathematical modeling. Medical, biology and math undergraduates and postgraduates, as well as basic and applied researchers attempting toextend their studies in collaboration with other specialists in interdi sciplinary teams, will find practical information here. Biomedical specialists could be interested in historical aspects of cancer treatment and prevention,mechanisms of carcinogenesis, cancer risk factors, cancer mortality and morbidity trends in the U.S . over a more than 50-year period, as well as specific features of cancer histotypes, and recent approaches to cancer prevention.Readers interested in analytic aspects can find information on existing and innovative approaches used in interdisciplinary st udies such as stochastic process models, microsimulation of interventions, and empirical Bayes approaches.This book was written by authors with different backgrounds who teamed in an interdisciplinary group. Kenneth G. Manton, Ph.D. (Demography) is Resear ch Professor of Demographic Studies at Duke University (Durham, NC). He was Head ofthe W.H.O. Collaborating Center for Research and Training in the Methods of Assessing Risk and Forecasting Health Status Trends. He has authored more than 450 peer-reviewed publications, including several books. Igor Akushevich, Ph.D.(Theoretical and Mathematical Physics), Center for Population Health and Aging at Duke University, authored more than 70 peer-reviewed publi
Note:Springer eBooks
Contents:Preface
Introduction: Cancer contra human: cohabitation with casualties?
Cancer modeling: how far can we move?
Cancer risk factors
Standard and innovative statistical methods for empirically analyzing cancer morbidity and mortality
Stochastic methods of analysis
U.S. cancer morbidity and mortality risks
U.S. cancer morbidity: modeling age
patterns of cancer histotypes
Risk factors intervention
Cancer prevention
Conclusion/outlook
Appendices
ISBN:9780387781938
Series:e-books
Series:SpringerLink (Online service)
Series:Statistics for Biology and Health, 1431-8776
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Oncology , Epidemiology , Bioinformatics , Demography
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Call number:SPRINGER-2008-9783540789116:ONLINE Show nearby items on shelf
Title:Mathematical Epidemiology [electronic resource]
Author(s): Fred Brauer
Pauline Driessche
Jianhong Wu
Date:2008
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Based on lecture notes of two summer schools with a mixed audience from mathematical sciences, epidemiology and public health, this volume offers a comprehensive introduction to basic ideas and techniques in modeling infectiousdiseases, for the compa rison of strategies to plan for an anticipated epidemic or pandemic, and to deal with a disease outbreak in real time. It covers detailed case studies for diseases including pandemic influenza, West Nile virus,and childhood diseases. Models for other dise ases including Severe Acute Respiratory Syndrome, fox rabies, and sexually transmitted infections are included as applications. Its chapters are coherent and complementary independent units.In order to accustom students to look at the current literature a nd to experience different perspectives, no attempt has been made to achieve united writing style or unified notation. Notes on some mathematical background (calculus,matrix algebra, differential equations, and probability) have been prepared and may be d ownloaded at the web site of the Centre for Disease Modeling (www.cdm.yorku.ca )
Note:Springer eBooks
Contents:and General Framework
A Light Introduction to Modelling Recurrent Epidemics
Compartmental Models in Epidemiology
An Introduction to Stochastic Epidemic Models
Advanced Modeling and Heterogeneities
An Introduction to Networks in Epidemic Modeling
Deterministic Compartmental Models: Extensions of Basic Models
Further Notes on the Basic Reproduction Number
Spatial Structure: Patch Models
Spatial Structure: Partial Differential Equations Models
Continuous
Time Age
Structured Models in Population Dynamics and Epidemiology
Distribution Theory, Stochastic Processes an
ISBN:9783540789116
Series:e-books
Series:SpringerLink (Online service)
Series:Lecture Notes in Mathematics, 0075-8434 : v1945
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Epidemiology , Differentiable dynamical systems , Differential Equations , Genetics Mathematics , Distribution (Probability theory)
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Call number:SPRINGER-2008-9780387781679:ONLINE Show nearby items on shelf
Title:Statistical Methods for Environmental Epidemiology with R [electronic resource] : A Case Study in Air Pollution and Health
Author(s): Francesca Dominici
Roger D Peng
Date:2008
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
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Note:Advances in statistical methodology and computing have played an important role in allowing researchers to more accurately assess the health effects of ambient air pollution. The methods and software developed in this area areapplicable to a wide arr ay of problems in environmental epidemiology. This book provides an overview of the methods used for investigating the health effects of air pollution and gives examples and case studies in R which demonstratethe application of those methods to real data. The book will be useful to statisticians, epidemiologists, and graduate students working in the area of air pollution and health and others analyzing similar data. The authors describe thedifferent existing approaches to statistical modeling and cover ba sic aspects of analyzing and understanding air pollution and health data. The case studies in each chapter demonstrate how to use R to apply and interpret differentstatistical models and to explore the effects of potential confounding factors. A working k nowledge of R and regression modeling is assumed. In-depth knowledge of R programming is not required to understand and run the examples.Researchers in this area will find the book useful as a ``live'' reference. Software for all of the analyses in the bo ok is downloadable from the web and is available under a Free Software license. The reader is free to run theexamples in the book and modify the code to suit their needs. In addition to providing the software for developing the statistical models, the aut hors provide the entire database from the National Morbidity Mortality and Air PollutionStudy (NMMAPS) in a convenient R package. With the database, readers can run the examples and experiment with their own methods and ideas. Roger D. Peng is an Assistan t Professor in the Department of Biostatistics at the Johns HopkinsBloomberg School of Public Health. He is a prominent researcher in the areas of air pollution and health risk assessment and statistica
Note:Springer eBooks
Contents:Overview of the data
Overview of statistical modeling
Statistical issues related to air pollution and health
Summarizing evidence of the health effects of air pollution
Case studies
ISBN:9780387781679
Series:e-books
Series:SpringerLink (Online service)
Series:Use R
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics
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Call number:SPRINGER-2008-9780387728353:ONLINE Show nearby items on shelf
Title:The Frailty Model [electronic resource]
Author(s): Luc Duchateau
Paul Janssen
Date:2008
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Clustered survival data are encountered in many scientific disciplines including human and veterinary medicine, biology, epidemiology, public health and demography. Frailty models provide a powerful tool to analyse clusteredsurvival data. In contrast to the large number of research publications on frailty models, relatively few statistical software packages contain frailty models. It is demanding for statistical practitioners and graduate students tograsp a good knowledge on frailty models from the e xisting literature. This book provides an in-depth discussion and explanation of the basics of frailty model methodology for such readers. The discussion includes parametric andsemiparametric frailty models and accelerated failure time models. Common tech niques to fit frailty models include the EM-algorithm, penalised likelihood techniques, Laplacian integration and Bayesian techniques. More advanced frailtymodels for hierarchical data are also included. Real-life examples are used to demonstrate how part icular frailty models can be fitted and how the results should be interpreted. The programs to fit all the worked-out examples in thebook are available from the Springer website with most of the programs developed in the freeware packages R and Winbugs. T he book starts with a brief overview of some basic concepts in classical survival analysis, collecting what isneeded for the reading on the more complex frailty models. Luc Duchateau is Associate Professor of Statistics at the Faculty of Veterinary Medici ne of the Ghent University, Belgium. He is board member of the Quetelet Society (BelgianRegion of the International Biometric Society) and of the International Biometric Society Channel Network. He has collaborated extensively with physicians in oncology and allergy, public health workers and veterinarians, and is anauthor of numerous papers in statistical, medical and veterinarian journals. Paul Janssen is Professor of Statistics at the Centre for Stat
Note:Springer eBooks
Contents:Parametric proportional hazards models with gamma frailty
Alternatives for the frailty model
Frailty distributions
The semiparametric frailty model
Multifrailty and multilevel models
Extensions of the frailty model
ISBN:9780387728353
Series:e-books
Series:SpringerLink (Online service)
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Oncology , Emerging infectious diseases , Epidemiology , Computer simulation , Biometrics
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Call number:SPRINGER-2007-9781402063008:ONLINE Show nearby items on shelf
Title:Problems of High Altitude Medicine and Biology [electronic resource]
Author(s): Almaz Aldashev
Robert Naeije
Date:2007
Publisher:Dordrecht : Springer Netherlands
Size:1 online resource
Note:Springer e-book platform
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Note:This book is directly derived from a NATO-sponsored international meeting on problems of high altitude medicine and biology, which was held on the shores of lake of Issyk-Kul, in Kyrghyzstan, in June 5-6, 2006. It was a surprisefor several European a nd North and South-American scientists to discover the still on-going momentum high level altitude physiology research, which was extremely active but insufficiently acknowledged in this remote Central Asiancountry at the time of the USSR. Accordingly, th e setting was perfect for numerous positive scientific interactions, exchanges of ideas, and structuring of new international collaborations. Overall, the meeting was an ideal mix of cellbiology, integrative physiology and medical applications. Hypoxia is and remains a major public health issue in many populated mountainous areas all over the world. We are sure that this book will be become a long-lasting essentialreference
Note:Springer eBooks
Contents:1. 45 Years of mountain medicine
2. High altitude pulmonary hypertension and chronic mountain sickness
3. The Cellular effects of hypoxia on the pulmonary circulation
4. Angiogenesis and chronic hypoxic pulmonary hypertension
5. Tetrahydrobiopterin and pulmonary hypertension
6. Hypoxia
induced proliferation of human pulmonary arterial smooth muscle cell is involved in the suppression of cyclin
dependent kinase inhibitors
7. Pulmonary adaptation to high altitude in wild mammals
8. Lung at high altitude: between physiology and pathology
9. Sildenafil and hypoxic pulmonary
ISBN:9781402063008
Series:e-books
Series:SpringerLink (Online service)
Series:Mathematics and Statistics (Springer-11649)
Keywords: Mathematics , Cardiology , Pneumology , Sports medicine , Physiology Mathematics
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Call number:SPRINGER-2007-9780387728995:ONLINE Show nearby items on shelf
Title:evaluating clinical research [electronic resource] : All that glitters is not gold
Author(s): Bengt D Furberg
Curt D Furberg
Date:2007
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
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Note:The objective of this book is to make its readers better informed and more critical consumers of clinical research to help them recognize the strengths and the weaknesses of scientific publications. In doing so, the reader willbe able to distinguish patient-important and methodologically sound studies from those having limitations in design, conduct and interpretation. There are no prerequisites for reading this book. The text is basic and has no statisticalformulas. Key take-home messages are listed at the end of each chapter. The large number of cartoons has two purposes: First, to make the text easier to read and generate a few laughs and, second, to underscore specific points,sometimes in a provocative way. Bengt D. Furberg, MD, PhD is board-cert ified in internal medicine. After spending a decade as medical director in the pharmaceutical industry, he now serves as medical consultant, evaluating the safetyand efficacy of pharmaceutical products and medical devices and promoting evidence-based medi cine. His brother, Curt D. Furberg, MD, PhD, is Professor in the Division of Public Health Sciences, Wake Forest University School ofMedicine, Winston-Salem, NC, USA. After arriving in the United States from Sweden, he worked at the National Heart, Lung, and Blood Institute of the National Institutes of Health for 12 years. He is co-author of Fundamentals ofClinical Trials with Lawrence M. Friedman and David L. DeMets. His areas of interest are clinical trials, evidence-based medicine and drug safety. The authors have acquired much of their knowledge about clinical studies through thetrial and error method. Thus, they have personal experience with many of the problems they describe
Note:Springer eBooks
Contents:What is the Purpose of This Book?
Why is Benefit
to
Harm Balance Essential to Treatment Decisions?
What are the Strengths of Randomized Controlled Clinical Trials?
What are the Weaknesses of Randomized Controlled Clinical Trials?
Do Meta
Analyses Provide the Ultimate Truth?
What are the Strengths of Observational Studies?
What are the Weaknesses of Observational Studies?
Were the Scientific Questions Specified in Advance?
Were the Treatment Groups Comparable Initially?
Why is Blinding/Masking So Important?
How is Symptomatic Improvement Measured?
is it Really P
ISBN:9780387728995
Series:e-books
Series:SpringerLink (Online service)
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Toxicology , Quality of Life , Quality of Life Research
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Call number:SPRINGER-2007-9780387713939:ONLINE Show nearby items on shelf
Title:Correlated Data Analysis: Modeling, Analytics, and Applications [electronic resource]
Author(s): Peter X.-K Song
Date:2007
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
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Note:This book presents some recent developments in correlated data analysis. It utilizes the class of dispersion models as marginal components in the formulation of joint models for correlated data. This enables the book to handle abroader range of data types than those analyzed by traditional generalized linear models. One example is correlated angular data. This book provides a systematic treatment for the topic of estimating functions. Under this framework,both generalized estimating equations (GEE) a nd quadratic inference functions (QIF) are studied as special cases. In addition to marginal models and mixed-effects models, this book covers topics on joint regression analysis based onGaussian copulas and generalized state space models for longitudinal data from long time series. Various real-world data examples, numerical illustrations and software usage tips are presented throughout the book. This book has evolvedfrom lecture notes on longitudinal data analysis, and may be considered suitable as a te xtbook for a graduate course on correlated data analysis. This book is inclined more towards technical details regarding the underlying theory andmethodology used in software-based applications. Therefore, the book will serve as a useful reference for tho se who want theoretical explanations to puzzles arising from data analyses or deeper understanding of underlying theoryrelated to analyses. Peter Song is Professor of Statistics in the Department of Statistics and Actuarial Science at the University of Wa terloo. Professor Song has published various papers on the theory and modeling of correlated dataanalysis. He has held a visiting position at the University of Michigan School of Public Health (Ann Arbor, Michigan)
Note:Springer eBooks
Contents:Introduction and examples
Dispersion models
Inference functions
Modeling correlated data
Marginal generalized linear models
Vector generalized linear models
Mixed
effects models: likelihood
based inference
Mixed
effects models: Bayesian inference
Linear predictors
Generalized state space models
Generalized state space models for longitudinal binomial data
Generalized state space models for longitudinal count data
Missing data in longitudinal studies
ISBN:9780387713939
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Series in Statistics, 0172-7397
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Mathematical statistics
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Call number:SPRINGER-2007-9780387698106:ONLINE Show nearby items on shelf
Title:The Statistical Analysis of Recurrent Events [electronic resource]
Author(s): Richard J Cook
Jerald F Lawless
Date:2007
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Recurrent event data arise in diverse fields such as medicine, public health, insurance, social science, economics, manufacturing and reliability. The purpose of this book is to present models and statistical methods for theanalysis of recurrent even t data. No single comprehensive treatment of these areas currently exists. The authors provide broad but detailed coverage of the major approaches to analysis, while also emphasizing the modeling assumptionsthat they are based on. Thus, they consider impo rtant models such as Poisson and renewal processes, with extensions to incorporate covariates or random effects. More general intensity-based models are also considered, as well assimpler models that focus on rate or mean functions. Parametric, nonparamet ric and semiparametric methodologies are all covered, with clear descriptions of procedures for estimation, testing and model checking. Important practicaltopics such as observation schemes and selection of individuals for study, the planning of randomize d experiments, events of several types, and the prediction of future events are considered. Methods of modeling and analysis areillustrated through many examples taken from health research and industry. The objectives and interpretations of different anal yses are discussed in detail, and issues of robustness are addressed. Statistical analysis of the examplesis carried out with S-PLUS software and code is given for some examples. This book is directed at graduate students, researchers, and applied statist icians working in industry, government or academia. Some familiarity with survivalanalysis is beneficial since survival software is used to carry out many of the analyses considered. This book can be used as a textbook for a graduate course on the analysi s of recurrent events or as a reference for a more generalcourse on event history analysis. Problems are given at the end of chapters to reinforce the material presented and to provide additional backgr
Note:Springer eBooks
Contents:Models and Frameworks for Analysis of Recurrent Events
Methods Based on Counts and Rate Functions
Analysis of Gap Times
General Intensity
Based Models
Multitype Recurrent Events
Observation Schemes Giving Incomplete or Selective Data
OtherTopics
ISBN:9780387698106
Series:e-books
Series:SpringerLink (Online service)
Series:Statistics for Biology and Health, 1431-8776
Series:Mathematics and Statistics (Springer-11649)
Keywords: Medicine , Epidemiology , Mathematical statistics , System safety , Econometrics , Social sciences Methodology
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Call number:SPRINGER-2006-9780387352091:ONLINE Show nearby items on shelf
Title:Statistical Methods in Counterterrorism [electronic resource] : Game Theory, Modeling, Syndromic Surveillance, and Biometric Authentication
Author(s): Alyson G Wilson
Gregory D Wilson
David H Olwell
Date:2006
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:All the data was out there to warn us of this impending attack, why didn't we see it? This was a frequently asked question in the weeks and months after the terrorist attacks on the World Trade Center and the Pentagon onSeptember 11, 2001. In the wak e of the attacks, statisticians moved quickly to become part of the national response to the global war on terror. This book is an overview of the emerging research program at the intersection of nationalsecurity and statistical sciences. A wide range of talented researchers address issues in . Syndromic Surveillance---How do we detect and recognize bioterrorist events? . Modeling and Simulation---How do we better understand andexplain complex processes so that decision makers can take the best course of action? . Biometric Authentication---How do we pick the terrorist out of the crowd of faces or better match the passport to the traveler? . Game Theory---Howdo we understand the rules that terrorists are playing by? This book includes technical treatments of statistical issues that will be of use to quantitative researchers as well as more general examinations of quantitative approaches tocounterterrorism that will be accessible to decision makers with stronger policy backgrounds. Dr. Alyson G. Wilson is a statistician and the technical lead for DoD programs in the Statistical Sciences Group at Los Alamos NationalLaboratory. Dr. Gregory D. Wilson is a rhetorician and ethnographer in the Statistical Sciences Group at Los Alamos National Laboratory. Dr. Dav id H. Olwell is chair of the Department of Systems Engineering at the Naval PostgraduateSchool in Monterey, California
Note:Springer eBooks
Contents:Game Theory
Game Theory in an Age of Terrorism: How Can Statisticians Contribute?
Combining Game Theory and Risk Analysis in Counterterrorism: A Smallpox Example
Game
Theoretic and Reliability Methods in Counterterrorism and Security
Biometric Authentication
Biometric Authentication
Towards Statistically Rigorous Biometric Authentication Using Facial Images
Recognition Problem of Biometrics: Nonparametric Dependence Measures and Aggregated Algorithms
Syndromic Surveillance
Data Analysis Research Issues and Emerging Public Health Biosurveillance Directions
Current
ISBN:9780387352091
Series:e-books
Series:SpringerLink (Online service)
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Optical pattern recognition , Mathematics , Operations research , Mathematical statistics , Economics, Mathematical
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Call number:SPRINGER-2006-9780387277820:ONLINE Show nearby items on shelf
Title:Statistical Monitoring of Clinical Trials [electronic resource] : Fundamentals for Investigators
Author(s): Lemuel A Moy
Date:2006
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Statistical Monitoring of Clinical Trials: Fundamentals for Investigators introduces the investigator and statistician to monitoring procedures in clinical research. Clearly presenting the necessary background with limited use ofmathematics, this boo k increases the knowledge, experience, and intuition of investigations in the use of these important procedures now required by the many clinical research efforts. The author provides motivated clinicalinvestigators the background, correct use, and interp retation of these monitoring procedures at an elementary statistical level. He defines terms commonly used such as group sequential procedures and stochastic curtailment innon-mathematical language and discusses the commonly used procedures of Pocock, OBr ienFleming, and LanDeMets. He discusses the notions of conditional power, monitoring for safety and futility, and monitoring multiple endpointsin the study. The use of monitoring clinical trials is introduced in the context of the evolution of clinical re search and one chapter is devoted to the more recent Bayesian procedures. Dr. Lemuel A. Moy, M.D., Ph.D. is a physicianand a biostatistician at the University of Texas School of Public Health. He is a diplomat of the National Board of Medical Examiners an d is currently Professor of Biostatistics at the University of Texas School of Public Health inHouston where he holds a full time faculty position. Dr. Moy has carried out cardiovascular research for twenty years and continues to be involved in the design , execution and analysis of clinical trials, both reporting to andserving on many Data Monitoring Committees. He has served in several clinical trials sponsored by both the U.S. government and private industry. In addition, Dr. Moy has served as statistic ian/epidemiologist for six years on both theCardiovascular and Renal Drug Advisory Committee to the Food and Drug Administration and the Pharmacy Sciences Advisory Committee to the FDA. H
Note:Springer eBooks
Contents:Here, there be dragons
The basis of statistical reasoning in medicine
Probability tools and stopping rules
Issues and intuitions in path analysis
Group sequential analysis procedures
Looking forward: conditional power
Safety and futility
Bayesian statistical monitoring
ISBN:9780387277820
Series:e-books
Series:SpringerLink (Online service)
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Neurosciences , Epidemiology
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Call number:SPRINGER-2006-9780387260235:ONLINE Show nearby items on shelf
Title:Probability, Statistics and Modelling in Public Health [electronic resource]
Author(s): Mikhail Nikulin
Daniel Commenges
Catherine Huber
Date:2006
Publisher:Boston, MA : Springer US
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Probability, Statistics and Modelling in Public Health consists of refereed contributions by expert biostatisticians that discuss various probabilistic and statistical models used in public health. Many of them are based on thework of Marvin Zelen of the Harvard School of Public Health. Topics discussed include models based on Markov and semi-Markov processes, multi-state models, models and methods in lifetime data analysis, accelerated failure models,design and analysis of clinical trials, Bayesian methods, pharmaceutical and environmental statistics, degradation models, epidemiological methods, screening programs, early detection of diseases, and measurement and analysis ofquality of life. Audience This book is intended for researchers interested i n statistical methodology in the biomedical field
Note:Springer eBooks
Contents:Forward and Backward Recurrence Times and Length Biased Sampling: Age Specific Models
Difference between Male and Female Cancer Incidence Rates: How Can It Be Explained?
Non
parametric estimation in degradation
renewal
failure models
The Impact of Dementia and Sex on the Disablement in the Elderly
Nonparametric Estimation for Failure Rate Functions of Discrete Time semi
Markov Processes
Some recent results on joint degradation and failure time modeling
Estimation in a Markov chain regression model with missing covariates
Tests of Fit based on Products of Spacings
A Surv
ISBN:9780387260235
Series:e-books
Series:SpringerLink (Online service)
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics
Availability:Click here to see Library holdings or inquire at Circ Desk (x3401)
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Call number:SPRINGER-2005-9780387291505:ONLINE Show nearby items on shelf
Title:Survival Analysis [electronic resource] : A Self-Learning Text
Author(s): David G Kleinbaum
Mitchel Klein
Date:2005
Edition:Second Edition
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:This greatly expanded second edition of Survival Analysis- A Self-learning Text provides a highly readable description of state-of-the-art methods of analysis of survival/event-history data. This text is suitable for researchersand statisticians work ing in the medical and other life sciences as well as statisticians in academia who teach introductory and second-level courses on survival analysis. The second edition continues to use the unique lecture-bookformat of the first (1996) edition with the ad dition of three new chapters on advanced topics: Chapter 7: Parametric Models Chapter 8: Recurrent events Chapter 9: Competing Risks. Also, the Computer Appendix has been revised to providestep-by-step instructions for using the computer packages STATA (V ersion 7.0), SAS (Version 8.2), and SPSS (version 11.5) to carry out the procedures presented in the main text. The original six chapters have been modified slightly toexpand and clarify aspects of survival analysis in response to suggestions by students, colleagues and reviewers, and to add theoretical background, particularly regarding the formulation of the (partial) likelihood functions forproportional hazards, stratified, and extended Cox regression models David Kleinbaum is Professor of Epidemiology at the Rollins School of Public Health at Emory University, Atlanta, Georgia. Dr. Kleinbaum is internationally known forinnovative textbooks and teaching on epidemiological methods, multiple linear regression, logistic regression, and survival analysis. He has provided extensive worldwide short-course training in over 150 short courses on statisticaland epidemiological methods. He is also the author of ActivEpi (2002), an interactive computer-based instructional text on fundamentals of epidemiology, whic h has been used in a variety of educational environments including distancelearning. Mitchel Klein is Research Assistant Professor with a joint appointment in the Department of Environmental and Occup
Note:Springer eBooks
Contents:Introduction to Survival Analysis
Kaplan
Meier Survival Curves and the Log
Rank Test
The Cox Proportional Hazards Model and Its Characteristics
Evaluating the Proportional Hazards Assumption
The Stratified Cox Procedure
Extension of the Cox Proportional Hazards Model for Time
Dependent Variables
Parametric Survival Models
Recurrent Events Survival Analysis
Competing Risks Survival Analysis
ISBN:9780387291505
Series:e-books
Series:SpringerLink (Online service)
Series:Statistics for Biology and Health, 1431-8776
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Epidemiology
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Call number:SPRINGER-2005-9780387283142:ONLINE Show nearby items on shelf
Title:Modeling Longitudinal Data [electronic resource]
Author(s): Robert E Weiss
Date:2005
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Longitudinal data are ubiquitous across Medicine, Public Health, Public Policy, Psychology, Political Science, Biology, Sociology and Education, yet many longitudinal data sets remain improperly analyzed. This book teaches the artand statistical scie nce of modern longitudinal data analysis. The author emphasizes specifying, understanding, and interpreting longitudinal data models. He inspects the longitudinal data graphically, analyzes the time trend andcovariates, models the covariance matrix, and t hen draws conclusions. Covariance models covered include random effects, autoregressive, autoregressive moving average, antedependence, factor analytic, and completely unstructured modelsamong others. Longer expositions explore: an introduction to and cri tique of simple non-longitudinal analyses of longitudinal data, missing data concepts, diagnostics, and simultaneous modeling of two longitudinal variables.Applications and issues for random effects models cover estimation, shrinkage, clustered data, mode ls for binary and count data and residuals and residual plots. Shorter sections include a general discussion of how computationalalgorithms work, handling transformed data, and basic design issues. This book requires a solid regression course as backgroun d and is particularly intended for the final year of a Biostatistics or Statistics Masters degree curriculum.The mathematical prerequisite is generally low, mainly assuming familiarity with regression analysis in matrix form. Doctoral students in Biostati stics or Statistics, applied researchers and quantitative doctoral students indisciplines such as Medicine, Public Health, Public Policy, Psychology, Political Science, Biology, Sociology and Education will find this book invaluable. The book has many fig ures and tables illustrating longitudinal data andnumerous homework problems. The associated web site contains many longitudinal data sets, examples of computer code, and labs to re-enforce the material
Note:Springer eBooks
Contents:to Longitudinal Data
Plots
Simple Analyses
Critiques of Simple Analyses
The Multivariate Normal Linear Model
Tools and Concepts
Specifying Covariates
Modeling the Covariance Matrix
Random Effects Models
Residuals and Case Diagnostics
Discrete Longitudinal Data
Missing Data
Analyzing Two Longitudinal Variables
Further Reading
ISBN:9780387283142
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Texts in Statistics, 1431-875X
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Mathematical statistics , Economics Statistics
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Call number:SPRINGER-2004-9783662053676:ONLINE Show nearby items on shelf
Title:Methods in Modern Biophysics
Author(s): Bengt Nölting
Date:2004
Size:1 online resource (254 p.)
Note:10.1007/978-3-662-05367-6
Contents:1 The three-dimensional structure of proteins -- 2 Liquid chromatography of biomolecules -- 3 Mass spectrometry -- 4 X-ray structural analysis -- 5 Protein infrared spectroscopy -- 6 Electron microscopy -- 7 Scanning probe microscopy
-- 8 Biophysical nanotechnology -- 9 Proteomics: high throughput protein functional analysis -- 10 Ion mobility spectrometry -- 11 Microwave auditory effects and the theoretical concept of thought transmission technology -- 12
Conclusions -- References
ISBN:9783662053676
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Physics , Biotechnology , Bioorganic chemistry , Physical chemistry , Medicine , Biochemistry , Biophysics , Biological physics , Physics , Biophysics and Biological Physics , Bioorganic Chemistry , Biotechnology , Physical Chemistry , Medicine/Public Health, general , Biochemistry, general
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Call number:SPRINGER-2004-9781461302179:ONLINE Show nearby items on shelf
Title:Applied Bayesian Statistical Studies in Biology and Medicine
Author(s):
Date:2004
Size:1 online resource (258 p.)
Note:10.1007/978-1-4613-0217-9
Contents:1. Some reflections on the current state of statistics -- 2. Answering two biological questions with a latent class model via MCMC applied to capture-recapture data -- 3. On the Bayesian inference of the Hardy-Weinberg equilibrium
model -- 4. Identifying a Bayesian Network for the problem “Hospital and families: the analysis of patient satisfaction with their stay in hospital” -- 5. Reliability of GIST diagnosis based on partial information -- 6. Comparing two
groups or treatments-a Bayesian approach -- 7. Two experimental settings in clinical trials: predictive criteria for choosing the sample size in interval estimation -- 8. Attributing a paleoanthropological specimen to a prehistoric
population: a Bayesian approach with multivariate B-spline functions -- 9. An example of the subjectivist statistical method for learning from data: Why do whales strand when they do? -- 10. Development and communication of Bayesan
methodology for medical device clinical trials -- 11. An adaptive SIR algorithm for Bayesian multilevel inference on categorical data -- 12. Age at death diagnosis by cranial suture obliteration: a Bayesian approach -- 13. Bayesian
estimation of restriction fragment length from electrophoretic analysis
ISBN:9781461302179
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Statistics , Human genetics , Public health , Biomathematics , Anthropology , Statistics , Statistics for Life Sciences, Medicine, Health Sciences , Public Health , Mathematical and Computational Biology , Anthropology , Human Genetics
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