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SPIRES-BOOKS: FIND KEYWORD PSYCHOMETRICS *END*INIT* use /tmp/qspiwww.webspi1/11737.169 QRY 131.225.70.96 . find keyword psychometrics ( in books using www Cover
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Call number:SPRINGER-2014-9789401788250:ONLINE Show nearby items on shelf
Title:Measurement and Probability [electronic resource] : A Probabilistic Theory of Measurement with Applications
Author(s): Giovanni Battista Rossi
Date:2014
Publisher:Dordrecht : Springer Netherlands : Imprint: Springer
Size:1 online resource
Note:Measurement plays a fundamental role both in physical and behavioral sciences, as well as in engineering and technology: it is the link between abstract models and empirical reality and is a privileged method of gatheringinformation from the real wor ld. Is it possible to develop a single theory of measurement for the various domains of science and technology in which measurement is involved? This book takes the challenge by addressing the followingmain issues: What is the meaning of measurement? How do we measure? What can be measured? A theoretical framework that could truly be shared by scientists in different fields, ranging from physics and engineering to psychology isdeveloped. The future in fact will require greater collaboration between scienc e and technology and between different sciences. Measurement, which played a key role in the birth of modern science, can act as an essentialinterdisciplinary tool and language for this new scenario. A sound theoretical basis for addressing key problems i n measurement is provided. These include perceptual measurement, the evaluation of uncertainty, the evaluation ofinter-comparisons, the analysis of risks in decision-making and the characterization of dynamical measurement. Currently, increasing attention is paid to these issues due to their scientific, technical, economic and social impact. Thebook proposes a unified probabilistic approach to them which may allow more rational and effective solutions to be reached. Great care was taken to make the text a s accessible as possible in several ways. Firstly, by giving preferenceto as interdisciplinary a terminology as possible secondly, by carefully defining and discussing all key terms. This ensures that a wide readership, including people from different mat hematical backgrounds and different understandingsof measurement can all benefit from this work. Concerning mathematics, all the main results are preceded by intuitive discussions and illustrated by si
Contents:Part I: General Problems
1 Measurability
2 Uncertainty
Part II: Theory
3 The Measurement Scale: Deterministic Framework
4 The Measurement Scale: Probabilistic Approach
5 The Measurement Process
6 Inference in Measurement
7 Multidimensional Measurements
Part III: Applications
8 Perceptual Measurement
9 The Evaluation of Measurement Uncertainty
10 Evaluating Inter
Comparisons
11 Measurement
Based Decisions
12 Dynamic Measurement
Appendix
Bibliography
ISBN:9789401788250
Series:eBooks
Series:SpringerLink
Series:Springer Series in Measurement Science and Technology, 2198-7807
Series:Physics and Astronomy (Springer-11651)
Keywords: Mathematics , Engineering , Psychometrics
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Call number:SPRINGER-2014-9781493903177:ONLINE Show nearby items on shelf
Title:Test Equating, Scaling, and Linking [electronic resource] : Methods and Practices
Author(s): Michael J Kolen
Robert L Brennan
Date:2014
Edition:3rd ed. 2014
Publisher:New York, NY : Springer New York : Imprint: Springer
Size:1 online resource
Note:This book provides an introduction to test equating, scaling, and linking, including those concepts and practical issues that are critical for developers and all other testing professionals. In addition to statisticalprocedures, successful equating, scaling, and linking involves many aspects of testing, including procedures to develop tests, to administer and score tests, and to interpret scores earned on tests. Test equating methods are used withmany standardized tests in education and psychology to ensure that scores from multiple test forms can be used interchangeably. Test scaling is the process of developing score scales that are used when scores on standardized testsare reported. In test linking, scores from two or more tests are related to one another. Linking has received much recent attention, due largely to investigations of linking similarly named tests from different test publishers or testsconstructed for different purposes. In recent years, researchers from the education, psychology, an d statistics communities have contributed to the rapidly growing statistical and psychometric methodologies used in test equating,scaling, and linking. In addition to the literature covered in previous editions, this new edition presents coverage of signi ficant recent research. In order to assist researchers, advanced graduate students and testing professionals,examples are used frequently, and conceptual issues are stressed. New material includes model determination in log-linear smoothing, in-depth pres entation of chained linear and equipercentile equating, equating criteria, test scoring,and a new section on scores for mixed-format tests. In the third edition, each chapter contains a reference list, rather than having a single reference list at the end of the volume The themes of the third edition include: * thepurposes of equating, scaling and linking and their practical context * data collection designs * statistical methodology * designing r
Contents:Introduction and Concepts
Observed Score Equating Using the Random Groups Design
Random Groups Smoothing in Equipercentile Equating
Nonequivalent Groups Linear Methods
Nonequivalent Groups Equipercentile Methods
Item Response Theory Methods
Standard Errors of Equating
Practical Issues in Equating
Score Scales
Linking
Appendices
Answers to Exercises
Computer Programs
Index
ISBN:9781493903177
Series:eBooks
Series:SpringerLink
Series:Statistics for Social and Behavioral Sciences
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Educational tests and measurements , Psychometrics
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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-2011-9783642205842:ONLINE Show nearby items on shelf
Title:Permutation Testing for Isotonic Inference on Association Studies in Genetics [electronic resource]
Author(s): Luigi Salmaso
Rosa Arboretti
Livio Corain
Dario Mazzaro
Date:2011
Publisher:Berlin, Heidelberg : Springer Berlin Heidelberg
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:

.

Note:Springer eBooks
Contents:Introduction
Association Studies in Genetics
The Nonparametric Permutation Methodology
Statistical Problems of Allelic Association
Power and Sample Size Simulations
Case Study
Conclusions
References
ISBN:9783642205842
Series:e-books
Series:SpringerLink (Online service)
Series:SpringerBriefs in Statistics
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Human genetics , Biotechnology , Pharmacy , Cytology Research_xMethodology , Psychometrics
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Call number:SPRINGER-2011-9781441999375:ONLINE Show nearby items on shelf
Title:Statistical Modeling of the National Assessment of Educational Progress [electronic resource]
Author(s): Irit Aitkin
Murray Aitkin
Date:2011
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:The purpose of this book is to evaluate a new approach to the analysis and reporting of the large-scale surveys for the National Assessment of Educational Progress carried out for the National Center for Education Statistics. Theneed for a new approa ch was driven by the demands for secondary analysis of the survey data by researchers who needed analyses more detailed than those published by NCES, and the need to accelerate the processing and publication ofresults from the surveys. This new approach i s based on a full multilevel statistical and psychometric model for students responses to the test items, taking into account the design of the survey, the backgrounds of the students,and the classes, schools and communities in which the students were loc ated. The authors detail a fully integrated single model that incorporates both the survey design and the psychometric model by extending the traditional form ofthe psychometric model to accommodate the design structure while allowing for student, teacher , and school covariates
Note:Springer eBooks
Contents:Theories of Data Analysis and Statistical Inference
The Current Design and Analysis
Psychometric and Survey Models
Technical Reports Data Analyses and Simulation Studies
1986 NAEP Math Survey
Analysis of All 1986Math Iems
2005 NAEP Math Survey Texas
2005 NAEP Math Survey California
Conclusions
1986 Survey Results, 30 Item Subscale
1986 Survey Results, Full 79 Items
Model Parameter Estimates and SEs, 2005 Texas Survey
Model Parameter Estimates and SEs, 2005 California survey
ISBN:9781441999375
Series:e-books
Series:SpringerLink (Online service)
Series:Statistics for Social and Behavioral Sciences
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Educational tests and measurements , Psychometrics
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Call number:SPRINGER-2011-9781441993892:ONLINE Show nearby items on shelf
Title:Looking Back [electronic resource] : Proceedings of a Conference in Honor of Paul W. Holland
Author(s): Neil J Dorans
Sandip Sinharay
Date:2011
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:In 2006, Paul W. Holland retired from Educational Testing Service (ETS) after a career spanning five decades. In 2008, ETS sponsored a conference, Looking Back, honoring his contributions to applied and theoretical psychometricsand statistics. Lookin g Back attracted a large audience that came to pay homage to Paul Holland and to hear presentations by colleagues who worked with him in special ways over those 40+ years. This book contains papers based on thesepresentations, as well as vignettes provide d by Paul Holland before each section. The papers in this book attest to how Paul Holland's pioneering ideas influenced and continue to influence several fields such as social networks, causalinference, item response theory, equating, and DIF. He applied statistical thinking to a broad range of ETS activities in test development, statistical analysis, test security, and operations. The original papers contained in thisbook provide historical context for Paul Hollands work alongside commentary on some of h is major contributions by noteworthy statisticians working today
Note:Springer eBooks
Contents:The Contributions of Paul Holland
Algebraic Statistics for p1 Random Graph Models
Mr. Holland's Networks: A Brief Review of the Importance of Statistical Studies of Local Subgraphs or One Small Tune in a Large Opus
Some of My Favorite Things About Working at ETS
Bayesian Analysis of a Two
Group Randomized Encouragement Design
The Role of Nonparametric Analysis in Assessment Modeling: Then and Now
What Aspects of the Design of an Observational Study Affect Its Sensitivity to Bias From Covariates That Were Not Observed?
The Origins of Procedures for Using Differential Item F
ISBN:9781441993892
Series:e-books
Series:SpringerLink (Online service)
Series:Lecture Notes in Statistics, 0930-0325 : v202
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Mathematics , Educational tests and measurements , Social sciences Methodology , Psychometrics
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Call number:SPRINGER-2011-9780387981383:ONLINE Show nearby items on shelf
Title:Statistical Models for Test Equating, Scaling, and Linking [electronic resource]
Author(s): Alina A Davier
Date:2011
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:The goal of this book is to emphasize the formal statistical features of the practice of equating, linking, and scaling. The book encourages the view and discusses the quality of the equating results from the statisticalperspective (new models, robus tness, fit, testing hypotheses, statistical monitoring) as opposed to placing the focus on the policy and the implications, which although very important, represent a different side of the equatingpractice. The book contributes to establishing equating as a theoretical field, a view that has not been offered often before. The tradition in the practice of equating has been to present the knowledge and skills needed as acraft, which implies that only with years of experience under the guidance of a knowledg eable practitioner could one acquire the required skills. This book challenges this view by indicating how a good equating framework, a soundunderstanding of the assumptions that underlie the psychometric models, and the use of statistical tests and stati stical process control tools can help the practitioner navigate the difficult decisions in choosing the final equatingfunction. This book provides a valuable reference for several groups: (a) statisticians and psychometricians interested in the theory beh ind equating methods, in the use of model-based statistical methods for data smoothing, and in theevaluation of the equating results in applied work (b) practitioners who need to equate tests, including those with these responsibilities in testing compani es, state testing agencies, and school districts and (c) instructors inpsychometric, measurement, and psychology programs. Dr. Alina A. von Davier is a Strategic Advisor and a Director of Special Projects in Research and Development at Educational Testing Service (ETS). During her tenure at ETS, she hasled an ETS Research Initiative called Equating and Applied Psychometrics and has directed the Global Psychometric Services Center. The cent
Note:Springer eBooks
Contents:Overview
A Statistical Perspective on Equating Test Scores (Alina A. von Davier)
Part I: Research Questions and Data Collection Designs
Equating Test Scores: Toward Best Practices Neil J. Dorans, Tim P. Moses, and Daniel R. Eignor)
Scoring and Scaling Educational Tests Michael J. Kolen, Ye Tong, and Robert L. Brennan)
Statistical Models for Vertical Linking James E. Carlson)
An Empirical Example of Change Analysis by Linking Longitudinal Item Response Data From Multiple Tests (John J. McArdle and Kevin J. Grimm)
How to Average Equating Functions, If You Must (Paul W. Holla
ISBN:9780387981383
Series:e-books
Series:SpringerLink (Online service)
Series:Statistics for Social and Behavioral Sciences
Series:Mathematics and Statistics (Springer-11649)
Keywords: Education , Educational tests and measurements , Statistics , Psychometrics
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Call number:SPRINGER-2010-9781441907424:ONLINE Show nearby items on shelf
Title:Bayesian Item Response Modeling [electronic resource] : Theory and Applications
Author(s): Jean-Paul Fox
Date:2010
Edition:First
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
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Note:This book presents a thorough treatment and unified coverage of Bayesian item response modeling with applications in a variety of disciplines, including education, medicine, psychology, and sociology. Breakthroughs in computingtechnology have made th e Bayesian approach particularly useful for many response modeling problems. Free from computational constraints, realistic and state-of-the-art latent variable response models are considered for complexassessment and survey data to solve real-world probl ems. The Bayesian framework described provides a unified approach for modeling and inference, dealing with (nondata) prior information and information across multiple data sources.The book discusses methods for analyzing item response data and the complex relationships commonly associated with human response behavior and features Self-contained introduction to Bayesian item response modeling and a coverageof extending standard models to handle complex assessment data A thorough overview of Bayesian esti mation and testing methods for item response models, where MCMC methods are emphasized Numerous examples that cover a wide rangeof application areas, including education, medicine, psychology, and sociology Datasets and software (S+, R, and WinBUGS code ) of the models and methods presented in the book are available on www.jean-paulfox.com Bayesian ItemResponse Modeling is an excellent book for research professionals, including applied statisticians, psychometricians, and social scientists who analyze it em response data from a Bayesian perspective. It is a guide to the growing areaof Bayesian response modeling for researchers and graduate students, and will also serve them as a good reference. Jean-Paul Fox is Associate Professor of Measurement and Data Analysis, University of Twente, The Netherlands. His mainresearch activities are in several areas of Bayesian response modeling. Dr. Fox has published numerous articles in the areas of Bayes
Note:Springer eBooks
Contents:Introduction to Bayesian response modeling
Bayesian hierarchical response modeling
Basic elements of Bayesian statistics
Estimation of Bayesian item response models
Assessment of Bayesian item response models
Multilevel item response theory models
Random item effects models
Response time item response models
Randomized item response models
ISBN:9781441907424
Series:e-books
Series:SpringerLink (Online service)
Series:Statistics for Social and Behavioral Sciences
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Epidemiology , Educational tests and measurements , Marketing , Social sciences Methodology , Psychometrics
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Call number:SPRINGER-2010-9780387927107:ONLINE Show nearby items on shelf
Title:Comparing Distributions [electronic resource]
Author(s): Olivier Thas
Date:2010
Publisher:New York, NY : Springer New York : Imprint: Springer
Size:1 online resource
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Note:Comparing Distributions refers to the statistical data analysis that encompasses the traditional goodness-of-fit testing. Whereas the latter includes only formal statistical hypothesis tests for the one-sample and the K-sampleproblems, this book pres ents a more general and informative treatment by also considering graphical and estimation methods. A procedure is said to be informative when it provides information on the reason for rejecting the nullhypothesis. Despite the historically seemingly diffe rent development of methods, this book emphasises the similarities between the methods by linking them to a common theory backbone. This book consists of two parts. In the first partstatistical methods for the one-sample problem are discussed. The second part of the book treats the K-sample problem. Many sections of this second part of the book may be of interest to every statistician who is involved incomparative studies. The book gives a self-contained theoretical treatment of a wide range of goodness-o f-fit methods, including graphical methods, hypothesis tests, model selection and density estimation. It relies on parametric,semiparametric and nonparametric theory, which is kept at an intermediate level the intuition and heuristics behind the methods a re usually provided as well. The book contains many data examples that are analysed with the cd R-packagethat is written by the author. All examples include the R-code. Because many methods described in this book belong to the basic toolbox of almost ever y statistician, the book should be of interest to a wide audience. In particular, thebook may be useful for researchers, graduate students and PhD students who need a starting point for doing research in the area of goodness-of-fit testing. Practitioners and applied statisticians may also be interested because of themany examples, the R-code and the stress on the informative nature of the procedures. Olivier Thas is Associate Professor of Biostatistics
Note:Springer eBooks
Contents:One
Sample Problems
Preliminaries (Building Blocks)
Graphical Tools
Smooth Tests
Methods Based on the Empirical Distribution Function
Two
Sample and K
Sample Problems
Preliminaries (Building Blocks)
Graphical Tools
Some Important Two
Sample Tests
Smooth Tests
Methods Based on the Empirical Distribution Function
Two Final Methods and Some Final Thoughts
ISBN:9780387927107
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Series in Statistics, 0172-7397
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Data mining , Statistical methods , Operations research , Social sciences Methodology , Psychometrics
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Call number:SPRINGER-2010-9780387854618:ONLINE Show nearby items on shelf
Title:Elements of Adaptive Testing [electronic resource]
Author(s): Wim J van der Linden
Cees A.W Glas
Date:2010
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
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Note:The arrival of the computer in educational and psychological testing has led to the current popularity of adaptive testing---a testing format in which the computer uses statistical information about the test items toautomatically adapt their selectio n to a real-time update of the test takers ability estimate. This book covers such key features of adaptive testing as item selection and ability estimation, adaptive testing with multidimensionalabilities, sequencing adaptive test batteries, multistage a daptive testing, item-pool design and maintenance, estimation of item and item-family parameters, item and person fit, as well as adaptive mastery and classification testing.It also shows how these features are used in the daily operations of several larg e-scale adaptive testing programs. Wim J. van der Linden is Chief Research Scientist at CTB/McGraw-Hill, Monterey, CA. His specialization is psychometrictheory and methods, and he has been an active researcher of adaptive testing throughout his career. Fo r Springer, he wrote Linear Models for Optimal Test Design (2005) and co-edited Handbook of Modern Item ResponseTheory (1997). He isa past president of the Psychometric Society and recipient of lifetime achievement awards from the National Council for Mea surement in Education (NCME) and the Association of Test Publishers (ATP). Cees A. W. Glas is Professor ofSocial Science Research Methodology, University of Twente, the Netherlands. His specialization is psychometric theory and methods, with an emphasis o n item response theory, adaptive testing, model fit analysis, and missing data.Professor Glas is a co-author of Educational Evaluation, Assessment, and Monitoring (Swets & Zetlinger, 2003). Currently, he is a member of the Editorial Board of Psychometrika and serves as a technical consultant to the OECD programsfor international student assessment (PISA) and the assessment of adult competencies (PIAAC)
Note:Springer eBooks
Contents:Item selection and ability estimation in adaptive testing
Constrained adaptive testing with shadow tests
Principles of multidimensional adaptive testing
Multidimensional adaptive testing with Kullback
Liebler information item selection
Sequencing an adaptive test battery
Adaptive tests for measuring anxiety and depression
MATHCAT: A flexible testing system in mathematics education for adults
Implementing the Graduate Management admission test computerized adaptive test
Designing and implementing a multistage adaptive test: The uniform CPA exam
A Japanese adaptive tes
ISBN:9780387854618
Series:e-books
Series:SpringerLink (Online service)
Series:Statistics for Social and Behavioral Sciences
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Educational tests and measurements , Psychometrics
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Call number:SPRINGER-2010-9780387688411:ONLINE Show nearby items on shelf
Title:Micro-Econometrics [electronic resource] : Methods of Moments and Limited Dependent Variables
Author(s): Myoung-jae Lee
Date:2010
Publisher:New York, NY : Springer New York
Size:1 online resource
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Note:This book introduces econometrics at the graduate level, and then specializes in micro-econometrics topics such as method of moments, limited and qualitative dependent variables, sample-selection models, panel data, nonparametricestimators and specif ication tests, and semi(non)-parametric methods. The coverage is up-to-date and broad as well as in depth. Many empirical examples are included along with a computer program appendix. Both graduate students andresearchers, applied or theoretical, in all d isciplines using observational data will find this book useful as a textbook as well as a research monograph for self-study and reference. The second edition is three times length of thefirst edition One chapter on liner equation systems has been added an d several new sections on panel data are new. Also sections for the following topics have been added: LDV's with endogenous regressors, competing risks, nonparametricsurvival and hazard function estimation, rank-based semiparametric methods, differencing- based semiparametric methods, semiparametric estimators for duration models, integrated moment specification tests, nonparametric control functionapproaches, nonparametric additive models, various transformation of response variables, and nonparametric sp ecification and significance tests. The appendix now contains the proofs for some important results in the main text and newsections for the following topics: review of mathematical and statistical backgrounds, nested logit, U-statistics, GMM with integra ted squared moments, goodness-of-fit tests for distribution functions, joint test for all quantiles,review on test, non-nested model test, stratified sampling and weighted M-estimator, empirical likelihood estimator, stochastic-process convergence and app lications, and bootstrap. The author, Myoung-jae Lee, is currently a Professorof Economics at Korea University, and has written Panel Data Econometrics: Methods-of-Moments and Limited Dependent Variable
Note:Springer eBooks
Contents:Methods of moments for single linear equation models
Methods of moments for multiple linear equation systems
M
Estimator and Maximum Likelihood Estimator (MLE)
Nonlinear models and estimators
Parametric methods for single equation LDV models
Parametric methods for multiple equation LDV Models
Kernel nonparametric estimation
Bandwidth
free semiparametric methods
Bandwidth
dependent semiparametric methods
ISBN:9780387688411
Series:e-books
Series:SpringerLink (Online service)
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Statistical methods , Economics Statistics , Econometrics , Marketing , Psychometrics
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Call number:SPRINGER-2009-9781441911483:ONLINE Show nearby items on shelf
Title:Statistical Analysis of Designed Experiments, Third Edition [electronic resource]
Author(s): Helge Toutenburg
Date:2009
Publisher:New York, NY : Springer New York
Size:1 online resource
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Note:This textbook presents the design and analysis of experiments that comprise the aspects of classical theory for continuous response, modern procedures for categorical response, and especially for correlated categorical response.For any design (indepe ndent and matched-pair response) the parametric and nonparametric tests depending on the data level are given. Complex designs, such as, for example, cross-over and repeated measures, are included at anintroductory and advanced manner. The problem of miss ing data is also handled with care and procedures in approaching this problem are proposed. Thus, this is an important resource/reference book for undergraduates and universityteachers, for statistical researchers in the pharmaceutical industry, or other industries, as well as for clinical research in medicine and dentistry. The third edition contains a new chapter on incomplete block designs that includesthe balanced incomplete block design and partially balanced incomplete block design in addition to th e general theory on incomplete block designs. The chapter Multifactor Experiments is extended and includes new topics onconfounding, partial confounding and fractional replications that are explained with examples. The more theoretical proofs of Chapters 3, 4 and 6 are put into an appendix. Helge Toutenburg is Professor of Statistics at the Universityof Munich. He has written nineteen books on linear models, statistical methods in quality engineering, and the analysis of designed experiments. He works on applications of statistics to the fields of medicine and engineering. Shalabhis Associate Professor of Statistics at the Indian Institute of Technology Kanpur. He has co-authored a book on linear models and co-edited a book on the recent developments in t he area of linear models. He works in the area of linearmodels, regression analysis and econometrics
Note:Springer eBooks
Contents:Introduction
Comparison of two samples
The linear regression model
Single
factor experiments with fixed and random effects
More restrictive designs
Incomplete block designs
Multifactor experiments
Models for categorical response variables
Repeated measures model
Cross
over design
Statistical analysis of incomplete data
ISBN:9781441911483
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Texts in Statistics, 1431-875X
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Bioinformatics , Statistical methods , Distribution (Probability theory) , Mathematical statistics , Econometrics , Psychometrics
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Call number:SPRINGER-2009-9780387981857:ONLINE Show nearby items on shelf
Title:Functional Data Analysis with R and MATLAB [electronic resource]
Author(s): James Ramsay
Giles Hooker
Spencer Graves
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:Scientists often collect samples of curves and other functional observations, and develop models where parameters are also functions. This volume in the UseR! Series is aimed at a wide range of readers, and especially those whowould like apply these techniques to their research problems. It complements Functional Data Analysis, Second Edition and Applied Functional Data Analysis: Methods and Case Studies by providing computer code in both the R and Matlablanguages for a set of data analyses that show case functional data analysis techniques. The authors make it easy to get up and running in new applications by adapting the code for the examples, and by being able to access the detailsof key functions within these pages. This book is accompanied by add itional web-based support at http://www.functionaldata.org for applying existing functions and developing new ones in either language. The companion 'fda' package forR includes script files to reproduce nearly all the examples in the book including all bu t one of the 76 figures. Jim Ramsay is Professor Emeritus at McGill University and is an international authority on many aspects of multivariateanalysis. He was President of the Statistical Society of Canada in 2002-3 and holds the Societys Gold Medal for his work in functional data analysis. His statistical work draws on his collaboration with researchers in biomechanics,chemical engineering, climatology, ecology, economics, human biology, medicine and psychology. Giles Hooker is Assistant Professor of B iological Statistics and Computational Biology at Cornell University. His research interests includestatistical inference in nonlinear dynamics, machine learning and computational statistics. Spencer Graves is an engineer with a PhD in Statistics and over 15 years experience using S-Plus and R to analyze data in a broad range ofapplications. He has made substantive contributions to several CRAN packages including fda and DierckxSpline.
Note:Springer eBooks
Contents:Introduction to functional data analysis
Essential comparisons of the Matlab and R languages
How to specify basis systems for building functions
How to build functional data objects
Smoothing: Computing curves from noisy data
Descriptions of functional data
Exploring variation: Functional principal and canonical components analysis
Registration: Aligning features for samples of curves
Functional linear models for scalar responses
Linear models for functional responses
Functional models and dynamics
ISBN:9780387981857
Series:e-books
Series:SpringerLink (Online service)
Series:Use R
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Data mining , Statistical methods , Mathematical statistics , Marketing , Psychometrics
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Call number:SPRINGER-2009-9780387899763:ONLINE Show nearby items on shelf
Title:Multidimensional Item Response Theory [electronic resource]
Author(s): M.D Reckase
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:Multidimensional Item Response Theory is the first book to give thorough coverage to this emerging area of psychometrics. The book describes the commonly used multidimensional item response theory (MIRT) models and the importantmethods needed for the ir practical application. These methods include ways to determine the number of dimensions required to adequately model data, procedures for estimating model parameters, ways to define the space for a MIRT model,and procedures for transforming calibration s from different samples to put them in the same space. A full chapter is devoted to methods for multidimensional computerized adaptive testing. The text is appropriate for an advanced coursein psychometric theory or as a reference work for those interest ed in applying MIRT methodology. A working knowledge of unidimensional item response theory and matrix algebra is assumed. Knowledge of factor analysis is also helpful.Mark D. Reckase is a professor of Measurement and Quantitative Methods in the College o f Education at Michigan State University. He has been president of the National Council of Measurement in Education, Vice President of Division D ofthe American Educational Research Association, on the Board of Trustees of the Psychometric Society, and th e editor of Applied Psychological Measurement and the Journal of Educational Measurement. He has been doing research in the areaof MIRT since 1972
Note:Springer eBooks
Contents:Introduction
Historical and intellectual underpinnings of multidimensional item response theory
Basic background in item response theory
Extension of item response theory to the multidimensional case
Estimation of item and person parameters
Linking of calibrations
Multidimensional models for computerized adaptive tests
Other applications of multidimensional item response theory
Future directions for multidimensional item response theory
ISBN:9780387899763
Series:e-books
Series:SpringerLink (Online service)
Series:Statistics for Social and Behavioral Sciences
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Computer simulation , Social sciences Methodology , Psychological tests and testing , Psychometrics
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Call number:SPRINGER-2008-9780387759616:ONLINE Show nearby items on shelf
Title:Wavelet Methods in Statistics with R [electronic resource]
Author(s): G. P Nason
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:Wavelet methods have recently undergone a rapid period of development with important implications for a number of disciplines including statistics. This book has three main objectives: (i) providing an introduction to waveletsand their uses in statis tics (ii) acting as a quick and broad reference to many developments in the area (iii) interspersing R code that enables the reader to learn the methods, to carry out their own analyses, and further developtheir own ideas. The book code is designed to wor k with the freeware R package WaveThresh4, but the book can be read independently of R. The book introduces the wavelet transform by starting with the simple Haar wavelet transform, andthen builds to consider more general wavelets, complex-valued wavelets , non-decimated transforms, multidimensional wavelets, multiple wavelets, wavelet packets, boundary handling, and initialization. Later chapters consider a varietyof wavelet-based nonparametric regression methods for different noise models and designs inc luding density estimation, hazard rate estimation, and inverse problems the use of wavelets for stationary and non-stationary time seriesanalysis and how wavelets might be used for variance estimation and intensity estimation for non-Gaussian sequences. T he book is aimed both at Masters/Ph.D. students in a numerate discipline (such as statistics, mathematics,economics, engineering, computer science, and physics) and postdoctoral researchers/users interested in statistical wavelet methods. Guy Nason is Pro fessor of Statistics at the University of Bristol. He has been actively involved inthe development of various wavelet methods in statistics since 1993. He was awarded the Royal Statistical Societys 2001 Guy Medal in Bronze for work on wavelets in statisti cs. He was the author of the first, free, generallyavailable wavelet package for statistical purposes in S and R (WaveThresh2)
Note:Springer eBooks
Contents:Wavelets, discrete wavelet transforms, non
decimated transforms, wavelet packet transforms, lifting transforms
Multiscale methods for denoising (wavelet shrinkage)
Locally stationary wavelet time series and texture modelling
Multiscale variable transformations for Gaussianization and variance stabilization
Miscellaneous topics
ISBN:9780387759616
Series:e-books
Series:SpringerLink (Online service)
Series:Use R!
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Data mining , Bioinformatics , Mathematical statistics , Econometrics , Psychometrics
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Call number:SPRINGER-2008-9780387732510:ONLINE Show nearby items on shelf
Title:Studying Human Populations [electronic resource] : An Advanced Course in Statistics
Author(s): Nicholas T Longford
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:Studying Human Populations is a textbook for graduate students and research workers in social statistics and related subject areas. It follows a novel curriculum developed around the basic statistical activities of sampling,measurement and inference. Statistics is defined broadly as making decisions in the presence of uncertainty that arises as a consequence of limited resources available for collecting information. A connecting link of the presentedmethods is the perspective of missing information, catering for a diverse class of problems that include nonresponse, imperfect measurement and causal inference. In principle, any problem too complex for our limited analytical toolkitcould be converted to a tractable problem if some additional information were available. Ingenuity is called for in declaring such (missing) information constructively, but the universe of problems that we can address is wide open, notlimited by a discrete set of procedures. The monograph aims to prepare the reader for the ca reer of an independent social statistician and to serve as a reference for methods, ideas for and ways of studying human populations:formulation of the inferential goals, design of studies, search for the sources of relevant information, analysis and pres entation of results. Elementary linear algebra and calculus are prerequisites, although the exposition is quiteforgiving, especially in the first few chapters. Familiarity with statistical software at the outset is an advantage, but it can be developed co ncurrently with studying the text. Nicholas T. Longford directs the statistical researchand consulting company SNTL in Reading, England. He had held senior research posts at the Educational Testing Service, Princeton, NJ, and De Montfort University, Leice ster, England. He was awarded the first Campion Fellowship by theRoyal Statistical Society (2000-2002). He is a member of the editorial boards of the British Journal of Mathematical and Statistical Psyc
Note:Springer eBooks
Contents:Anova and Ordinary Regression
Maximum Likelihood Estimation
Sampling Methods
The Bayesian Paradigm
Incomplete Data
Imperfect Measurement
Experiments and Observational Studies
Clinical Trials
Random Coefficients
Generalised Linear Models
Longitudinal and Time
Series Analysis
Meta
Analysis and Estimating Many Quantities
ISBN:9780387732510
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Texts in Statistics, 1431-875X
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Epidemiology , Electronic data processing , Computer simulation , Biometrics , Mathematical statistics , Psychometrics
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Call number:SPRINGER-2008-9780387731865:ONLINE Show nearby items on shelf
Title:Handbook of Multilevel Analysis [electronic resource]
Author(s): Jan de Leeuw
Erik Meijer
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:Multilevel analysis is the statistical analysis of hierarchically and non-hierarchically nested data. The simplest example is clustered data, such as a sample of students clustered within schools. Multilevel data are especiallyprevalent in the social and behavioral sciences and in the bio-medical sciences. The models used for this type of data are linear and nonlinear regression models that account for observed and unobserved heterogeneity at the variouslevels in the data. This book presents the stat e of the art in multilevel analysis, with an emphasis on more advanced topics. These topics are discussed conceptually, analyzed mathematically, and illustrated by empirical examples. Theauthors of the chapters are the leading experts in the field. Given the omnipresence of multilevel data in the social, behavioral, and biomedical sciences, this book is useful for empirical researchers in these fields. Prior knowledgeof multilevel analysis is not required, but a basic knowledge of regression analysis, (as ymptotic) statistics, and matrix algebra is assumed. Jan de Leeuw is Distinguished Professor of Statistics and Chair of the Department ofStatistics, University of California at Los Angeles. He is former president of the Psychometric Society, former editor of the Journal of Educational and Behavioral Statistics, founding editor of the Journal of Statistical Software, andeditor of the Journal of Multivariate Analysis. He is coauthor (with Ita Kreft) of Introducing Multilevel Modeling and a member of the Alb ert Gifi team who wrote Nonlinear Multivariate Analysis. Erik Meijer is Economist at the RANDCorporation and Assistant Professor of Econometrics at the University of Groningen. He is coauthor (with Tom Wansbeek) of the highly acclaimed book Measurement Er ror and Latent Variables in Econometrics
Note:Springer eBooks
Contents:to Multilevel Analysis
Bayesian Multilevel Analysis and MCMC
Diagnostic Checks for Multilevel Models
Optimal Designs for Multilevel Studies
Many Small Groups
Multilevel Models for Ordinal and Nominal Variables
Multilevel and Related Models for Longitudinal Data
Non
Hierarchical Multilevel Models
Multilevel Generalized Linear Models
Missing Data
Resampling Multilevel Models
Multilevel Structural Equation Modeling
ISBN:9780387731865
Series:e-books
Series:SpringerLink (Online service)
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Epidemiology , Mathematical statistics , Econometrics , Social sciences Methodology , Psychometrics
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Call number:SPRINGER-2007-9780387698137:ONLINE Show nearby items on shelf
Title:Permutation Methods [electronic resource] : A Distance Function Approach
Author(s): Paul W Mielke
Kenneth J Berry
Date:2007
Edition:Second
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:Most commonly-used parametric and permutation statistical tests, such as the matched-pairs t test and analysis of variance, are based on non-metric squared distance functions that have very poor robustness characteristics. Thissecond edition places i ncreased emphasis on the use of alternative permutation statistical tests based on metric Euclidean distance functions that have excellent robustness characteristics. These alternative permutation techniquesprovide many powerful multivariate tests includi ng multivariate multiple regression analyses. In addition to permutation techniques described in the first edition, this second edition also contains various new permutation statisticalmethods and studies that include resampling multiple contingency table analyses, analysis concerns involving log-linear models with small samples, an exact discrete analog of Fishers continuous method for combining P-values thatarise from small data sets, multiple dichotomous response analyses, problems regarding Fishers Z transformation for correlation analyses, and multivariate similarity comparisons between corresponding multiple categories of twosamples. Paul W. Mielke, Jr. is Professor of Statistics at Colorado State University, and a fellow of the American Statistical Association. Kenneth J. Berry is Professor of Sociology at Colorado State University
Note:Springer eBooks
Contents:Introduction
Description of MRPP
Additional MRPP applications
Description of MRBP
Regression analysis, prediction, and agreement
Goodness
of
Fit tests
Contingency tables
Multisample homogeneity tests
Selected permutation studies
ISBN:9780387698137
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Series in Statistics, 0172-7397
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Data mining , Biometrics , Mathematical statistics , Environmental toxicology , Psychometrics
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Call number:SPRINGER-2007-9780387498393:ONLINE Show nearby items on shelf
Title:Multivariate and Mixture Distribution Rasch Models [electronic resource] : Extensions and Applications
Author(s): Matthias Davier
Claus H Carstensen
Date:2007
Publisher:New York, NY : Springer New York
Size:1 online resource
Note:Springer e-book platform
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Note:This volume covers extensions of the Rasch model, one of the most researched and applied models in educational research and social science. This collection contains 22 chapters by some of the most recognized international expertsin the field. They co ver topics ranging from general model extensions to applications in fields as diverse as cognition, personality, organizational and sports psychology, and health sciences and education. The Rasch model is designedfor categorical data, often collected as e xaminees' responses to multiple tasks such as cognitive items from psychological tests or from educational assessments. The Rasch model's elegant mathematical form is suitable for extensionsthat allow for greater flexibility in handling complex samples of examinees and collections of tasks from different domains. In these extensions, the Rasch model is enhanced by additional structural elements that either account fordifferences between diverse populations or for differences among observed variables. Rese arch on extending well-known statistical tools like regression, mixture distribution, and hierarchical linear models has led to the adoption ofRasch model features to handle categorical observed variables. We maintain both perspectives in the volume and s how how these merged modelsRasch models with a more complex item or population structureare derived either from theRasch model or from a structural model, how they are estimated, and where they are applied. Matthias von Davier is a Senior Research Scienti st in the Research & Development Division at Educational Testing Service. He is the author ofWINMIRA, a software package for estimating latent class models, mixture distribution Rasch models, and hybrid Rasch models. The software grew out of his work with colleagues at the Methodology Department of the Institute for ScienceEducation (IPN) in Kiel, Germany. Von Davier's current research is concerned with extensions of Rasch models and more general
Note:Springer eBooks
Contents:Introduction: extending the Rasch model or abandoning the Rasch model, Matthias von Davier, Jrgen Rost, Claus H. Carstensen
Measurement models as narrative structures, Robert Mislevy, Chun
Wei Huang
Testing generalized RM's, Cees A.W. Glas
The mixed
coefficients multinomal logit model
a generalized form of the Rasch model, Raymond J. Adams, Margaret L. Wu
Loglinear multivariate mixture Rasch models, Henk Kelderman
Mixture distribution and hybrid Rasch models, Matthias von Davier, Kentaro Yamamoto
Application of the Saltus model to stage
like data: some appliations and curr
ISBN:9780387498393
Series:e-books
Series:SpringerLink (Online service)
Series:Statistics for Social and Behavioral Sciences
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Quality of Life , Quality of Life Research , Psychological tests and testing , Psychometrics
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Call number:SPRINGER-2007-9780387497716:ONLINE Show nearby items on shelf
Title:Linking and Aligning Scores and Scales [electronic resource]
Author(s): Neil J Dorans
Mary Pommerich
Paul W Holland
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:The comparability of measurements made in differing circumstances by different methods and investigators is a fundamental pre-condition for all of science. Successful applications of technology require comparable measurements.While the applications h erefocus on educational tests, score linking issues are directly applicable to medicine and many branches of behavioral science. Since the 1980s, the fields of educational and psychological measurement haveenhanced and widely applied techniques for produc ing linked scores that are comparable. The interpretation attached to a linkage depends on how the conditions of the linkage differ from the ideal. In this book, experts in statisticsand psychometrics describe classes of linkages, the history of score lin kings, data collection designs, and methods used to achieve sound score linkages. They describe and critically discuss applications to a variety of domainsincluding equating of achievement exams, linkages between computer-delivered exams and paper-and-pen cil exams, concordances between the current version of the SAT and its predecessor, concordances between the ACT and the SAT,vertical linkages of exams that span grade levels, and linkages of scales from high-stakes state assessments to the scales of the National Assessment of Educational Progress (NAEP). Dr. Neil J. Dorans is a Distinguished PresidentialAppointee at Educational Testing Service. During his 27 years at ETS, he has had primary responsibility for the statistical work associated with the AP, PSAT/NMSQT, and SAT exams. He was the architect for the recentered SATscales. He has guest edited special issues on score linking for Applied Measurement in Education, Applied Psychological Measurement, and the Journal of Educational Measurement. Dr. Mary Pommerich is a psychometrician in the PersonnelTesting Division of the Defense Manpower Data Center, where she works with the ASVAB (Armed Services Vocational Aptitude Battery) testing prog
Note:Springer eBooks
Contents:Overview
A framework and history for score linking
Data collection designs and linking procedures, Michael J. Kolen
Equating: best practices and challenges to best practices, Nancy S. Petersen
Practical problems in equating test scores: a practioner's perspective, Linda L. Cook
Potential solutions to practical equating issues, Alina A. von Davier
Score linking issues related to test content changes, Jinghua Liu and Michael E. Walker
Linking scores derived under different modes of test administration, Daniel R. Eignor
Tests in transition: discussion and synthesis, Robert
ISBN:9780387497716
Series:e-books
Series:SpringerLink (Online service)
Series:Statistics for Social and Behavioral Sciences
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Educational tests and measurements , Psychological tests and testing , Psychometrics
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Call number:SPRINGER-2006-9780387449562:ONLINE Show nearby items on shelf
Title:Selected Papers of Frederick Mosteller [electronic resource]
Author(s): Stephen E Fienberg
David C Hoaglin
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:Frederick Mosteller has inspired numerous statisticians and other scientists by his creative approach to statistics and its applications. This volume brings together 40 of his most original and influential papers, capturing thevariety and depth of hi s writings. The editors hope to share these with a new generation of researchers, so that they can build upon his insights and efforts. This volume of selected papers is a companion to the earlier volume AStatistical Model: Frederick Mosteller's Contribut ions to Statistics, Science, and Public Policy, edited by Stephen E. Fienberg, David C. Hoaglin, William H. Kruskal, and Judith M. Tanur (Springer-Verlag, 1990), and to Mosteller'sforthcoming autobiography, which will also be published by Springer-Verlag. It includes a biography and a comprehensive bibliography of Mosteller's books, papers, and other writings. Stephen E. Fienberg is Maurice Falk UniversityProfessor of Statistics and Social Science, in the Departments of Statistics and Machine Learning at Carnegie Mellon University, Pittsburgh, PA. David C. Hoaglin is Principal Scientist at Abt Associates Inc., Cambridge, MA
Note:Springer eBooks
Contents:Frederick MostellerA Brief Biography
Unbiased Estimates for Certain Binomial Sampling Problems with Applications
On Some Useful Inefficient Statistics
A k
Sample Slippage Test for an Extreme Population
The Uses and Usefulness of Binomial Probability Paper
The Education of a Scientific Generalist
Remarks on the Method of Paired Comparisons: I. The Least Squares Solution Assuming Equal Standard Deviations and Equal Correlations
Remarks on the Method of Paired Comparisons: II. The Effect of an Aberrant Standard Deviation When Equal Standard Deviations and Equal Corre
ISBN:9780387449562
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Series in Statistics, 0172-7397
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Educational tests and measurements , Mathematical statistics , Econometrics , Psychometrics
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Call number:SPRINGER-2006-9780387357683:ONLINE Show nearby items on shelf
Title:Finite Mixture and Markov Switching Models [electronic resource]
Author(s): Sylvia Frhwirth-Schnatter
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:The prominence of finite mixture modelling is greater than ever. Many important statistical topics like clustering data, outlier treatment, or dealing with unobserved heterogeneity involve finite mixture models in some way orother. The area of potent ial applications goes beyond simple data analysis and extends to regression analysis and to non-linear time series analysis using Markov switching models. For more than the hundred years since Karl Pearsonshowed in 1894 how to estimate the five parameters of a mixture of two normal distributions using the method of moments, statistical inference for finite mixture models has been a challenge to everybody who deals with them. In the pastten years, very powerful computational tools emerged for dealing with these models which combine a Bayesian approach with recent Monte simulation techniques based on Markov chains. This book reviews these techniques and covers the mostrecent advances in the field, among them bridge sampling techniques and reversible jump Ma rkov chain Monte Carlo methods. It is the first time that the Bayesian perspective of finite mixture modelling is systematically presented inbook form. It is argued that the Bayesian approach provides much insight in this context and is easily implemented in practice. Although the main focus is on Bayesian inference, the author reviews several frequentist techniques,especially selecting the number of components of a finite mixture model, and discusses some of their shortcomings compared to the Bayesian ap proach. The aim of this book is to impart the finite mixture and Markov switching approach tostatistical modelling to a wide-ranging community. This includes not only statisticians, but also biologists, economists, engineers, financial agents, market rese archer, medical researchers or any other frequent user of statisticalmodels. This book should help newcomers to the field to understand how finite mixture and Markov switching models are formulated, wha
Note:Springer eBooks
Contents:Finite Mixture Modelling
Statistical Inference for a Finite Mixture Model with Known Number of Components
Practical Bayesian Inference for A Finite Mixture Model With Known Number of Components
Statistical Inference for Finite Mixture Models Under Model Specification Uncertainty
Computational Tools for Bayesian Inference for Finite Mixture Models Under Model Specification Uncertainty
Finite Mixture Models With Normal Components
Data Analysis Based on Finite Mixtures
Finite Mixtures of Regression Models
Finite Mixture Models with Non
Normal Components
Finite Markov Mi
ISBN:9780387357683
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Series in Statistics, 0172-7397
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Computer science , Bioinformatics , Mathematical statistics , Econometrics , Psychometrics
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Call number:SPRINGER-2005-9781846281952:ONLINE Show nearby items on shelf
Title:Missing Data and Small-Area Estimation [electronic resource] : Modern Analytical Equipment for the Survey Statistician
Author(s): Nicholas T Longford
Date:2005
Publisher:London : Springer London
Size:1 online resource
Note:Springer e-book platform
Note:Springer 2013 e-book collections
Note:This book develops methods for two key problems in the analysis of large-scale surveys: dealing with incomplete data and making inferences about sparsely represented subdomains. The presentation is committed to two particularmethods, multiple imputat ion for missing data and multivariate composition for small-area estimation. The methods are presented as developments of established approaches by attending to their deficiencies. Thus the change to moreefficient methods can be gradual, sensitive to the management priorities in large research organisations and multidisciplinary teams and to other reasons for inertia. The typical setting of each problem is addressed first, and then theconstituency of the applications is widened to reinforce the view that the general method is essential for modern survey analysis. The general tone of the book is not from theory to practice, but from current practice to betterpractice. The third part of the book, a single chapter, presents a method for efficient estimation under model uncertainty. It is inspired by the solution for small-area estimation and is an example of from good practice to bettertheory. A strength of the presentation is chapters of case studies, one for each problem. Whenever possible, turning to exam ples and illustrations is preferred to the theoretical argument. The book is suitable for graduate studentsand researchers who are acquainted with the fundamentals of sampling theory and have a good grounding in statistical computing, or in conjunction wi th an intensive period of learning and establishing one's own a modern computing andgraphical environment that would serve the reader for most of the analytical work in the future. While some analysts might regard data imperfections and deficiencies, such as nonresponse and limited sample size, as someone else'sfailure that bars effective and valid analysis, this book presents them as respectable analytical and inferential challenges, opportunitie
Note:Springer eBooks
Contents:Prologue
Describing Incompleteness
Single Imputation and Related Methods
Multiple Imputation
Case Studies
Introduction
Models for Small Areas
Using Auxiliary Information
Using Small
Area Estimators
Case Studies
Model Selection
ISBN:9781846281952
Series:e-books
Series:SpringerLink (Online service)
Series:Statistics for Social Science and Public Policy
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Epidemiology , Computer simulation , Mathematical statistics , Psychometrics
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Call number:SPRINGER-2005-9780387290546:ONLINE Show nearby items on shelf
Title:Linear Models for Optimal Test Design [electronic resource]
Author(s): Wim J Linden
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:This book begins with a reflection on the history of test design--the core activity of all educational and psychological testing. It then presents a standard language for modeling test design problems as instances ofmulti-objective constrained optimi zation. The main portion of the book discusses test design models for a large variety of problems from the daily practice of testing, and illustrates their use with the help of numerous empiricalexamples. The presentation includes models for the assembly of tests to an absolute or relative target for their information functions, classical test assembly, test equating problems, item matching, test splitting, simultaneousassembly of multiple tests, tests with item sets, multidimensional tests, and adaptive test assembly. Two separate chapters are devoted to the questions of how to design item banks for optimal support of programs with fixed andadaptive tests. Linear Models for Optimal Test Design, which does not require any specific mathematical background, has been written to be a helpful resource on the desk of any test specialist. Wim J. van der Linden is Professor ofMeasurement and Data Analysis, University of Twente, The Netherlands. His specialization is psychometric theory and methods, and he has bee n an active researcher of item response theory throughout his career. His current research is ontest design, adaptive testing, test equating, and response-time modeling. Professor van der Linden is a past president of the Psychometric Society and a recipi ent of the NCME lifetime achievement award for his work on educationalmeasurement
Note:Springer eBooks
Contents:A Brief History of Test Theory and Design
Formulating Test Specifications
Modeling Test Assembly Problems
Solving Test Assembly Problems
Models for Assembling Single Tests
Models for Assembling Multiple Tests
Models for Assembling Tests with Items Sets
Models for Assembling Tests Measuring Multiple Abilities
Models for Adaptive Test Assembly
Designing Item Pools for Programs with Fixed Tests
Designing Item Pools for Programs with Adaptive Tests
Epilogue
ISBN:9780387290546
Series:e-books
Series:SpringerLink (Online service)
Series:Statistics for Social and Behavioral Sciences
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Educational tests and measurements , Psychometrics
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Call number:SPRINGER-2004-9781475743104:ONLINE Show nearby items on shelf
Title:Test Equating, Scaling, and Linking Methods and Practices
Author(s): Michael J Kolen
Date:2004
Edition:Second Edition
Size:1 online resource (549 p.)
Note:10.1007/978-1-4757-4310-4
Contents:1 Introduction and Concepts -- 2 Observed Score Equating Using the Random Groups Design -- 3 Random Groups—Smoothing in Equipercentile Equating -- 4 Nonequivalent Groups—Linear Methods -- 5 Nonequivalent Groups—Equipercentile Methods
-- 6 Item Response Theory Methods -- 7 Standard Errors of Equating -- 8 Practical Issues in Equating -- 9 Score Scales -- 10 Linking -- 11 Current and Future Challenges -- References -- Appendix A: Answers to Exercises -- Appendix B:
Computer Programs
ISBN:9781475743104
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Statistics , Assessment , Psychometrics , Statistics , Statistics for Social Science, Behavorial Science, Education, Public Policy, and , Assessment, Testing and Evaluation , Psychometrics
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Call number:SPRINGER-2004-9781475739909:ONLINE Show nearby items on shelf
Title:Explanatory Item Response Models A Generalized Linear and Nonlinear Approach
Author(s):
Date:2004
Size:1 online resource (382 p.)
Note:10.1007/978-1-4757-3990-9
Contents:1 A framework for item response models -- 2 Descriptive and explanatory item response models -- 3 Models for polytomous data -- 4 An Introduction to (Generalized (Non)Linear Mixed Models -- 5 Person regression models -- 6 Models with
item and item group predictors -- 7 Person-by-item predictors -- 8 Multiple person dimensions and latent item predictors -- 9 Latent item predictors with fixed effects -- 10 Models for residual dependencies -- 11 Mixture Models -- 12
Estimation and software -- Afterword
ISBN:9781475739909
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Statistics , Assessment , Psychometrics , Statistics , Statistics for Social Science, Behavorial Science, Education, Public Policy, and , Assessment, Testing and Evaluation , Psychometrics
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Call number:SPRINGER-2004-9780387217192:ONLINE Show nearby items on shelf
Title:The Kernel Method of Test Equating
Author(s): Alina A. von Davier
Date:2004
Size:1 online resource (230 p.)
Note:10.1007/b97446
Contents:and Notation -- and Notation -- The Kernel Method of Test Equating: Theory -- Data Collection Designs -- Kernel Equating: Overview, Pre-smoothing, and Estimation of r and s -- Kernel Equating: Continuization and Equating -- Kernel
Equating: The SEE and the SEED -- Kernel Equating versus Other Equating Methods -- The Kernel Method of Test Equating: Applications -- The Equivalent-Groups Design -- The Single-Group Design -- The Counterbalanced Design -- The NEAT
Design: Chain Equating -- The NEAT Design: Post-Stratification Equating
ISBN:9780387217192
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Assessment , Statistics , Econometrics , Psychometrics , Economics , Econometrics , Statistics for Social Science, Behavorial Science, Education, Public Policy, and , Assessment, Testing and Evaluation , Psychometrics
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Call number:SPRINGER-2001-9781475734560:ONLINE Show nearby items on shelf
Title:Generalizability Theory
Author(s): Robert L Brennan
Date:2001
Size:1 online resource (538 p.)
Note:10.1007/978-1-4757-3456-0
Contents:1 Introduction -- 2 Single-Facet Designs -- 3 Multifacet Universes of Admissible Observations and G Study Designs -- 4 Multifacet Universes of Generalization and D Study Designs -- 5 Advanced Topics in Univariate Generalizability
Theory -- 6 Variability of Statistics in Generalizability Theory -- 7 Unbalanced Random Effects Designs -- 8 Unbalanced Random Effects Designs—Examples -- 9 Multivariate G Studies -- 10 Multivariate D Studies -- 11 Multivariate
Unbalanced Designs -- 12 Multivariate Regressed Scores -- Appendices -- A. Degrees of Freedom and Sums of Squares for Selected Balanced Designs -- B. Expected Mean Squares and Estimators of Random Effects Variance Components for
Selected Balanced Designs -- C. Matrix Procedures for Estimating Variance Components and Their Variability -- D. Table for Simplified Use of Satterthwaite’s Procedure -- E. Formulas for Selected Unbalanced Random Effects Designs -- F.
Mini-Manual for GENOVA -- G. urGENOVA -- H. mGENOVA -- I. Answers to Selected Exercises -- References -- Author Index
ISBN:9781475734560
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Statistics , Assessment , Psychometrics , Statistics , Statistics for Social Science, Behavorial Science, Education, Public Policy, and , Assessment, Testing and Evaluation , Psychometrics
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Call number:SPRINGER-1994-9789401108003:ONLINE Show nearby items on shelf
Title:Proceedings of the First US/Japan Conference on the Frontiers of Statistical Modeling: An Informational Approach Volume 2 Multivariate Statistical Modeling
Author(s):
Date:1994
Size:1 online resource (417 p.)
Note:10.1007/978-94-011-0800-3
Contents:of Volume 2 -- Summary of Contributed Papers to Volume 2 -- 1. Some Aspects of Model-Selection Criteria -- 2. Mixture-Model Cluster Analysis Using Model Selection Criteria and a New Informational Measure of Complexity -- 3.
Information and Entropy in Cluster Analysis -- 4. Information-Based Validity Functionals for Mixture Analysis -- 5. Unsupervised Classification with Stochastic Complexity -- 6. Modelling Principal Components with Structure -- 7.
AIC-Replacements for Some Multivariate Tests of Homogeneity with Applications in Multisample Clustering and Variable Selection -- 8. High Dimensional Covariance Estimation: ‘Avoiding The Curse of Dimensionality’ -- 9. Categorical Data
Analysis by AIC -- 10. Longitudinal Data Models with Fixed and Random Effects -- 11. Multivariate Autoregressive Modeling for Analysis of Biomedical Systems with Feedback -- 12. A Simulation Study of Information Theoretic Techniques an
Hypothesis Tests in One Factor ANOVA -- 13. Roles of Fisher Type Information in Latent Trait Models -- 14. A Review of Applications of AIC in Psychometrics -- Index to Volume 2
ISBN:9789401108003
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Mathematics , Probabilities , Statistics , Mathematics , Probability Theory and Stochastic Processes , Statistical Theory and Methods
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Call number:SPRINGER-1993-9783642509742:ONLINE Show nearby items on shelf
Title:Information and Classification Concepts, Methods and Applications Proceedings of the 16th Annual Conference of the “Gesellschaft für Klassifikation e.V.” University of Dortmund, April 1–3, 1992
Author(s):
Date:1993
Size:1 online resource (517 p.)
Note:10.1007/978-3-642-50974-2
Contents:I: Data Analysis and Classification -- Classification Methods -- Hierarchical Clustering of Sampled Functions -- Spatial Clustering of Species Based on Quadrat Sampling -- A kn-Nearest Neighbour Algorithm for Unimodal Clusters --
Asymptotic Robustness in Cluster-Analysis for the Case of Tukey-Huber Distortions -- Choosing the Number of Component Clusters in the Mixture-Model Using a New Informational Complexity Criterion of the Inverse-Fisher Information Matrix
-- Fuzzy Classification -- Fuzzy Sets and Fuzzy Partitions -- Fuzzy Clustering by Minimizing the Total Hypervolume -- Conceptual Analysis -- Conceptual Data Systems -- Conceptual Clustering via Convex-Ordinal Structures -- Diagrams of
Similarity Lattices -- Approximate Galois Lattices of Formal Concepts -- Representation of Data by Pseudoline Arrangements -- Mathematical Characterizations -- A Relational Approach to Split Decomposition -- Some New Useful
Representations of Dissimilarities in Mathematical Classification -- Multidimensional Scaling -- A Comparison of Two Methods for Global Optimization in Multidimensional Scaling -- Directional Analysis of Three-Way Skew-Symmetric
Matrices -- Clustering in Low-Dimensional Space -- The Construction of Neighbour-Regions in Two Dimensions for Prediction with Multi-Level Categorical Variables -- Different Geometric Approaches to Correspondence Analysis of
Multivariate Data -- Nonlinear Biplots for Nonlinear Mappings -- Various Methods for Data Analysis -- Gradient Filtering Projections for Recovering Structures in Multivariate Data -- Classification with Set-Valued Decision Functions --
Canonical Discriminant Analysis: Comparison of Resampling Methods and Convex-Hull Approximation -- Nonparametric Prediction of Time Series on the Basis of Typical Course Patterns -- Moving Point Patterns: The Poisson Case -- II:
Information Retrieval, Knowledge Processing and Software -- Information Retrieval -- Representations, Models and Abstractions in Probabilistic Information Retrieval -- Fuzzy Graphs as a Basic Tool for Agglomerative Clustering and
Information Retrieval -- The Various Roles of Information Structures -- Neural Networks -- Classification Properties of Communicating Neural Networks -- Knowledge Extraction from Self-Organizing Neural Networks -- Self-Organizing
Neural Networks for Visualisation and Classification -- Expert Systems and Knowledge Processing -- HyDi: Integration of Hypermedia and Expert System Technology for Technical Diagnosis -- Classification and Learning of Similarity
Measures -- Context Sensitive Knowledge Processing -- An Efficient Application of a Rule-Based System -- Computational Linguistics -- Acquisition of Syntactical Knowledge from Text -- Generating Topic-Based Links in a Hypertext-System
for News -- Software -- Interactively Displaying Ultrametric and Additive Trees -- Anaglyphen 3D — A Program for the Interactive Representation of Three-Dimensional Perspective Plots of Statistical Data -- III: Applications and Special
Topics -- Sequence Data and Tree Reconstruction -- Discovering Consensus Molecular Sequences -- Alignment and Hierarchical Clustering Method for Strings -- More Reliable Phylogenies by Properly Weighted Nucleotide Substitutions --
Caminalcules and Didaktozoa: Imaginary Organisms as Test-Examples for Systematics -- Data Analysis and Informatics in Medicine -- Multivariate Analysis of the Process of Acclimation of Physiologic Variables -- Classification of EEG
Signals into General Stages of Anesthesia in Real-Time Using Autoregressive Models -- Automatic Segmentation and Classification of Multiparametric Image Data in Medicine -- Pseudoroots as Descriptors for a Thesaurus Based on Weidtman’s
Diagnosis Table of Pediatrics -- Special Topics - Thesauri, Archaeology, Musical Science and Psychometrics -- An Approach to a Space Related Thesaurus -- Classification of Archaeological Sands by Particle Size Analysis -- The Analysis
of Stratigraphic Data with Particular Reference to Zonation Problems -- Classification Criterion and the Universals in the Organization of a Musical Text -- A Two-Mode Clustering Study of Situations and Their Features
ISBN:9783642509742
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Keywords: Health informatics , Bioinformatics , Computational biology , Probabilities , Statistics , Economic theory , Economics , Economic Theory/Quantitative Economics/Mathematical Methods , Probability Theory and Stochastic Processes , Statistics, general , Health Informatics , Computer Appl. in Life Sciences
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Call number:SPRINGER-1981-9781468410839:ONLINE Show nearby items on shelf
Title:Intelligence and Learning
Author(s):
Date:1981
Size:1 online resource (624 p.)
Note:10.1007/978-1-4684-1083-9
Contents:Section 1. Introduction -- 1. Introduction and Overview -- 2. Intelligence and Learning -- 3. Recent Issues in the Developmental Approach to Mental Retardation -- 4. Reaction Time and Intelligence -- 5. Intelligence and Learning:
Specific and General Handicap -- Section 2. The Nature of Intelligence — Symposium -- 6. The Nature of Intelligence -- 7. The Primary Mental Ability -- 8. Genetic Differences in “g” and Real Life -- Section 3. The Nature of
Intelligence — Papers -- 9. Physiological Evidence that Demand for Processing Capacity Varies with Intelligence -- 10. Closure Factors: Evidence for Different Modes of Processing -- 11. Test Structure and Cognitive Style -- 12.
Intelligence and the Orienting Reflex -- Section 4. Individual Variability and Intelligence -- 13. Individual Differences in Memory Span -- 14. Towards a Symbiosis of Cognitive Psychology and Psychometrics -- 15. Development and
Modifiability of Adult Intellectual 169 Performance: An Examination of Cognitive Intervention in Later Adulthood -- 16. The Relationship Between Memory Span and Processing Speed -- Section 5. Piagetian Approaches -- 17. Cognitive
Mechanisms and Training -- 18. Training and Logic: Comment on Magali Bovet’s Paper -- 19. The Role of Social Experience in Cognitive Development -- 20. Knowledge Development and Memory Performance -- 21. Reasoning and Problem Solving
in Young Children -- 22. Logical Competence in Infancy: Object Percept or Object Concept? -- Section 6. Piaget and Development -- 23. Piagetian Perspective in Draw-A-House Tree Task: A Longitudinal Study of the Drawings of Rural
Children -- 24. Metacognition and Intelligence Theory -- 25. Adaptation to Equilibration: A More Complex Model of the Applications of Piaget’s Theory to Early Childhood Education -- 26. A Model of Cognitive Development -- 27. The Use
of a Piagetian Analysis of Infant Development to Predict Cognitive and Language Development at Two Years -- Section 7. Cognitive Psychological Analyses -- 28. Testing Process Theories of Intelligence -- 29. Coding and Planning
Processes -- 30. Process Theories: Form or Substance? A Discussion of the Papers by Butterfield, Das Jarman -- Section 8. Intelligence and Cognitive Processes -- 31. Toward a Unified Componential Theory of Human Intelligence: I. Fluid
Ability -- 32. Toward a Theory of Aptitude for Learning: I. Fluid and Crystallized Abilities and their Correlates -- Section 9. Reading Processes -- 33. Comparison of Reading and Spelling Strategies in Normal and Reading Disabled
Children -- 34. Active Perceiving and the Reflection-Impulsivity Dimension -- 35. Cognitive Strategies in Relation to Reading Disability -- 36. Comparative Efficacy of Group Therapy and Remedial Reading with Reading Disabled Children
-- 37. Coding Strategies and Reading Comprehension -- Section 10. Cross-Cultural Approaches -- 38. Cultural Systems and Cognitive Styles -- 39. Culture, Cognitive Tests and Cognitive Models: Pursuing Cognitive Universals by Testing
Across Cultures -- Section 11. Individual Differences and Cognition -- 40. Human Ageing and Disturbances of Memory Control Processes Underlying “Intelligent” Performance of Some Cognitive Tasks -- 41. Ability Factors and the Speed of
Information Processing -- 42. The Design of a Robot Mind: A Theoretical Approach To Issues In Intelligence -- 43. Cognitive Psychology and Psychometric Theory -- Section 12. Mental Retardation and Learing Disabilities -- 44. A
Comparison of Psychometric and Piagetian Assessments of Symbolic Functioning in Down’s Syndrome Children -- 45. A Comparison of the Conservation Acquisition of Mentally Retarded and Nonretarded Children -- 46. Generalization of a
Rehearsal Strategy in Mildly Retarded Children -- 47. Cognitive Processing in Learning Disabled and Normally Achieving Boys in a Goal-Oriented Task -- 48. Home Environment, Cognitive Processes, and Intelligence: A Path Analysis --
Section 13. Pathology of Intelligence -- 49. Inducing Flexible Thinking: The Problem of Access -- 50. Hemispheric Intelligence: The Case of the Raven Progressive Matrices -- Section 14. Intellectual Abilities -- 51. Individual
Differences in the Patterning of Curves of D.Q. and I.Q. Scores from 6 months to 17 Years -- 52. The Social Ecology of Intelligence in the British Isles, France and Spain -- 53. Verbal Ability, Attention, and Automaticity -- 54.
Ability and Strategy Differences in Map Learning -- Section 15. Information Processing -- 55. Information Processing — “Old Wine In New Bottles” or A Challenge to the Psychology of Learning and Intelligence? -- 56. General Intelligence
and Mental Speed: Their Relationship and Development -- 57. Presentation Mode and Organisational Strategies in Young Children’s Free Recall -- 58. Qualitative and Quantitative Aspects in the Development of Proportional Reasoning --
Name Index
ISBN:9781468410839
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Series:NATO Conference Series, III Human Factors : 14
Keywords: Science , Science, general , Science, general
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