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SPIRES-BOOKS: FIND KEYWORD PSYCHOLOGICAL TESTS AND TESTING *END*INIT* use /tmp/qspiwww.webspi1/23478.138 QRY 131.225.70.96 . find keyword psychological tests and testing ( in books using www Cover
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Call number:SPRINGER-2011-9781461406853:ONLINE Show nearby items on shelf
Title:R for SAS and SPSS Users [electronic resource]
Author(s): Robert A Muenchen
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:R is a powerful and free software system for data analysis and graphics, with over 4,000 add-on packages available. This book introduces R using SAS and SPSS terms with which you are already familiar. It demonstrates which of theadd-on packages are m ost like SAS and SPSS and compares them to R's built-in functions. It steps through over 50 programs written in all three packages, comparing and contrasting the packages' differing approaches. The glossary definesR terms using SAS/SPSS terminology and ag ain using R terminology. The table of contents and the index allow you to find equivalent R functions by looking up both SAS statements and SPSS commands. The second edition adds 216 pages ofnew topics. I found the book extremely helpfulThe material is la id out in a way that makes it very accessible. Because of this I recommend this book to any R user regardless of his or her familiarity with SAS or SPSS...For new Rusers it will demystify many aspects, and for existing R users it will have many answers to those questions you have been too afraid to ask in public. --The American Statistician an excellent introduction to Rthe bookmeticulously covers data management, data structures, programming, graphics and basic statistical analysis in R. The prose is cle ar, the examples tied to their SPSS and SAS analogs. The handling of both traditional and newerggplot2 graphics is comprehensive: SPSS and SAS users will undoubtedly find lots to like. --Information Management As a long time SAS user this book makes the task of transition to R much more palatable and appealing. Italso greatly reduces the time to get up and running in R effectively. --Technometrics It is great to see this book in a second edition. It serves nicely as an introduction to R, irrespective of whether they are familiar with SASor SPSS. I have long been a fan of programming by example and the book is full of excellent ones. --Graham Williams, Author, Data M
Note:Springer eBooks
Contents:Introduction
Installing and Updating R
Running R
Help and Documentation
Programming Language Basics
Data Acquisition
Selecting Variables
Selecting Observations
Selecting Variables and Observations
Data Management
Enhancing Your Output
Generating Data
Managing Your Files and Workspace
Graphics Overview
Traditional Graphics
Graphics with ggplot2
Statistics
Conclusion
ISBN:9781461406853
Series:e-books
Series:SpringerLink (Online service)
Series:Statistics and Computing, 1431-8784
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Computer science , Data mining , Computer graphics , Mathematical statistics , Social sciences Methodology , Psychological tests and testing
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Call number:SPRINGER-2010-9781441912138:ONLINE Show nearby items on shelf
Title:Design of Observational Studies [electronic resource]
Author(s): Paul R Rosenbaum
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:An observational study is an empiric investigation of effects caused by treatments when randomized experimentation is unethical or infeasible. Observational studies are common in most fields that study the effects of treatmentson people, including me dicine, economics, epidemiology, education, psychology, political science and sociology. The quality and strength of evidence provided by an observational study is determined largely by its design. Design ofObservational Studies is both an introduction to statistical inference in observational studies and a detailed discussion of the principles that guide the design of observational studies. Design of Observational Studies is divided intofour parts. Chapters 2, 3, and 5 of Part I cover concisely, in about one hundred pages, many of the ideas discussed in Rosenbaums Observational Studies (also published by Springer) but in a less technical fashion. Part II discussesthe practical aspects of using propensity scores and other tools to create a matched compari son that balances many covariates. Part II includes a chapter on matching in R. In Part III, the concept of design sensitivity is used toappraise the relative ability of competing designs to distinguish treatment effects from biases due to unmeasured cova riates. Part IV discusses planning the analysis of an observational study, with particular reference to Sir RonaldFishers striking advice for observational studies, make your theories elaborate. Paul R. Rosenbaum is the Robert G. Putzel Professor of Stati stics at the Wharton School of the University of Pennsylvania. He is a fellow of theAmerican Statistical Association. In 2003, he received the George W. Snedecor Award from the Committee of Presidents of Statistical Societies. He is a senior fellow of the Leonard Davis Institute of Health Economics and a ResearchAssociate at the Population Studies Center, both at the University of Pennsylvania. The second edition of his book, Observational Studi
Note:Springer eBooks
Contents:Beginnings
Dilemmas and Craftsmanship
Causal Inference in Randomized Experiments
Two Simple Models for Observational Studies
Competing Theories Structure Design
Opportunities, Devices, and Instruments
Transparency
Matching
A Matched Observational Study
Basic Tools of Multivariate Matching
Various Practical Issues in Matching
Fine Balance
Matching Without Groups
Risk
Set Matching
Matching in R
Design Sensitivity
The Power of a Sensitivity Analysis and Its Limit
Heterogeneity and Causality
Uncommon but Dramatic Responses to Treatment
Antic
ISBN:9781441912138
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Series in Statistics, 0172-7397
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Statistical methods , Mathematical statistics , Econometrics , Social sciences Methodology , Psychological tests and testing
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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
Note:Springer 2013 e-book collections
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-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-2009-9780387094182:ONLINE Show nearby items on shelf
Title:R for SAS and SPSS Users [electronic resource]
Author(s): Robert A Muenchen
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:R is a powerful and free software system for data analysis and graphics, with over 1,200 add-on packages available. This book introduces R using SAS and SPSS terms with which you are already familiar. It demonstrates which of theadd-on packages are m ost like SAS and SPSS and compares them to R's built-in functions. It steps through over 30 programs written in all three packages, comparing and contrasting the packages' differing approaches. The programs andpractice datasets are available for download. The glossary defines over 50 R terms using SAS/SPSS jargon and again using R jargon. The table of contents and the index allow you to find equivalent R functions by looking up both SASstatements and SPSS commands. When finished, you will be able to impor t data, manage and transform it, create publication quality graphics, and perform basic statistical analyses. Robert A. Muenchen is the manager of the StatisticalConsulting Center at the University of Tennessee and has 28 years of experience as a consulti ng statistician. He has served on the advisory boards of SPSS Inc. and the Statistical Graphics Corporation. This is a really great book. Itis easy to read, quite comprehensive, and would be extremely valuable to both regular R users and users of SAS and SPSS who wish to switch to or learn about RAn invaluable reference. - David Hitchcock, University of South CarolinaThanks for writing R for SAS and SPSS Users--it is a comprehensible and clever document. The graphics chapter is superb! - Tony N. Brown, Va nderbilt University This is a Rosetta Stone for SPSS and SAS users to start learning Rquickly and effectively. - Ralph O'Brien, ASA Fellow I am a professional SAS and SPSS programmer and found this book extremely useful. - Tony Chu, Public Policy Research Data Analyst
Note:Springer eBooks
Contents:Introduction. The five main parts of SAS and SPSS
Programming conventions
Typographic conventions
Installing & updating R
Running R
Help and documentation
Programming language basics
Data Acquisition
Selecting Variables
Var, Variables
Selecting observations
where, if select if, filter
Selecting both variables and observations
Converting data structures
Data management
Recoding variables. Value labels or formats (& measurement level)
Variable labels
Generating data
How R stores data
Managing your files and workspace
Graphics overview
ISBN:9780387094182
Series:e-books
Series:SpringerLink (Online service)
Series:Statistics and Computing, 1431-8784
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Computer science , Data mining , Computer graphics , Mathematical statistics , Social sciences Methodology , Psychological tests and testing
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Call number:SPRINGER-2008-9780387781914:ONLINE Show nearby items on shelf
Title:The Statistical Analysis of Functional MRI Data [electronic resource]
Author(s): Nicole Lazar
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:One of the most intriguing questions facing modern science is the inner workings of the human brain. Functional magnetic resonance imaging (fMRI) is a powerful tool used to study the human brain in action. The data produced frommapping the active pro cesses within the brain present many challenges to statisticians, computer scientists, engineers and other data analysts, due to their complex structure and the ever-increasing sophistication of the scientificquestions being posed by researchers. This boo k represents the first in-depth discussion of statistical methodology, which it couples with an introduction to the scientific background needed to understand the data. Starting from thebasic science - where fMRI data come from, why they are so complicate d, and the role statistics can play in designing and interpreting experiments - the book gives a detailed survey of the numerous methods that have been applied in thelast fifteen years. The analysis of fMRI data features many of the major issues of concer n in modern statistics, such as high dimensionality, multiple testing, and visualization. The array of techniques examined in the book ranges fromthe simple two-sample t-test and the general linear model to hierarchical spatiotemporal models, multivariate methods such as principal components analysis, and Bayesian approaches as they have been used in fMRI. Software, includingdescriptions of the most popular freeware packages and their capabilities, is also discussed. This book offers researchers who are i nterested in the analysis of fMRI data a detailed discussion from a statistical perspective that coversthe entire process from data collection to the graphical presentation of results. The book is a valuable resource for statisticians who want to learn mo re about this growing field, and for neuroscientists who want to learn more abouthow their data can be analyzed. Nicole A. Lazar is Professor of Statistics at the University of Georgia and affiliated fa
Note:Springer eBooks
Contents:The science of fMRI
Design of fMRI experiments
Noise and data preprocessing
Statistical issuesin fMRI data analysis
Basic statistical analysis
Temporal, spatial, and spatiotemporal models
Multivariate approaches
Basis function approaches
Bayesian methods in fMRI
Multiple testing in fMRI: the problem of thresholding
Additional statistical issues
Case study: eye motion data
Survey of major fMRI software packages
Glossary of fMRI terms
References
Index
ISBN:9780387781914
Series:e-books
Series:SpringerLink (Online service)
Series:Statistics for Biology and Health, 1431-8776
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Neurosciences , Bioinformatics , Psychological tests and testing
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Call number:SPRINGER-2008-9780387775012:ONLINE Show nearby items on shelf
Title:Statistical Learning from a Regression Perspective [electronic resource]
Author(s): Richard A Berk
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:Statistical Learning from a Regression Perspective considers statistical learning applications when interest centers on the conditional distribution of the response variable, given a set of predictors, and when it is important tocharacterize how the predictors are related to the response. As a first approximation, this is can be seen as an extension of nonparametric regression. Among the statistical learning procedures examined are bagging, random forests,boosting, and support vector machines. Respon se variables may be quantitative or categorical. Real applications are emphasized, especially those with practical implications. One important theme is the need to explicitly take intoaccount asymmetric costs in the fitting process. For example, in some s ituations false positives may be far less costly than false negatives. Another important theme is to not automatically cede modeling decisions to a fittingalgorithm. In many settings, subject-matter knowledge should trump formal fitting criteria. Yet anot her important theme is to appreciate the limitation of ones data and not apply statistical learning procedures that require morethan the data can provide. The material is written for graduate students in the social and life sciences and for researchers wh o want to apply statistical learning procedures to scientific and policy problems. Intuitive explanationsand visual representations are prominent. All of the analyses included are done in R. Richard Berk is Distinguished Professor of Statistics Emeritus f rom the Department of Statistics at UCLA and currently a Professor at the Universityof Pennsylvania in the Department of Statistics and in the Department of Criminology. He is an elected fellow of the American Statistical Association and the American Asso ciation for the Advancement of Science and has served in aprofessional capacity with a number of organizations such as the Committee on Applied and Theoretical Statistics for the National Research Co
Note:Springer eBooks
Contents:Statistical Learning as a Regression Problem
Regression Splines and Regression Smoothers
Classification and Regression Trees (CART)
Bagging
Random Forests
Boosting
Support Vector Machines
Broader Implications and a Bit of Craft Lore
ISBN:9780387775012
Series:e-books
Series:SpringerLink (Online service)
Series:Springer Series in Statistics, 0172-7397
Series:Mathematics and Statistics (Springer-11649)
Keywords: Statistics , Mathematical statistics , Social sciences Methodology , Psychological tests and testing
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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
Note:Springer 2013 e-book collections
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-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-1993-9781461227380:ONLINE Show nearby items on shelf
Title:Probability Models and Statistical Analyses for Ranking Data
Author(s):
Date:1993
Size:1 online resource (306 p.)
Note:10.1007/978-1-4612-2738-0
Contents:1 Ranking Models with Item Covariates -- 1.1 Introduction -- 1.2 Basic Ranking Models and Their Parameters -- 1.3 Ranking Models with Covariates -- 1.4 Estimation -- 1.5 Example -- 1.6 Discussion -- 1.7 Appendix -- 1.8 References -- 2
Nonparametric Methods of Ranking from Paired Comparisons -- 2.1 Introduction and Literature Review -- 2.2 The Proposed Method of Scoring -- 2.3 Distribution Theory and Tests of Significance for ??ij = pij -- 2.4 Ranking Methods -- 2.5
Numerical Example -- 2.6 References -- 3 On the Babington Smith Class of Models for Rankings -- 3.1 Introduction -- 3.2 Alternative Parametrizations and Related Models -- 3.3 Stochastic Transitivity and Item Preference -- 3.4 Examples
and Data Analysis -- 3.5 References -- 4 Latent Structure Models for Ranking Data -- 4.1 Introduction -- 4.2 Latent Class Analyses Based on the Bradley-Terry-Luce Model -- 4.3 Latent Class Analyses Based on a Quasi-independence Model
-- 4.4 Models that Allow for Association Between Choices within the Classes -- 4.5 References -- 5 Modelling and Analysing Paired Ranking Data -- 5.1 Introduction -- 5.2 Two Models -- 5.3 Estimation and Hypothesis Testing -- 5.4
Analysis of Simulated Data Sets -- 5.5 Analysis of Rogers Data -- 5.6 References -- 6 Maximum Likelihood Estimation in Mallows’s Model Using Partially Ranked Data -- 6.1 Introduction -- 6.2 Notation -- 6.3 Maximum Likelihood Estimation
Using the EM Algorithm -- 6.4 Example -- 6.5 Discussion -- 6.6 References -- 7 Extensions of Mallows’ ? Model -- 7.1 Introduction -- 7.2 The General Model -- 7.3 Ties, Partial Rankings -- 7.4 Example: Word Association -- 7.5 Example:
APA Voting -- 7.6 Example: ANOVA -- 7.7 Discussion of Contrasts -- 7.8 Appendix -- 7.9 References -- 8 Rank Correlations and the Analysis of Rank-Based Experimental Designs -- 8.1 Introduction -- 8.2 Distance Based Measures of
Correlation -- 8.3 The Problem of m Rankings -- 8.4 The Two Sample Problem -- 8.5 The Problem of m Rankings for a Balanced Incomplete Block Design -- 8.6 The Problem of m Rankings for Cyclic Designs -- 8.7 Measuring Correlation Between
Incomplete Rankings -- 8.8 References -- 9 Applications of Thurstonian Models to Ranking Data -- 9.1 Introduction -- 9.2 The Ranking Model -- 9.3 Modeling ? -- 9.4 Subpopulations -- 9.5 Model Estimation and Tests -- 9.6 Applications --
9.7 Discussion -- 9.8 References -- 10 Probability Models on Rankings and the Electoral Process -- 10.1 Introduction -- 10.2 Electoral Systems -- 10.3 Models for Permutations -- 10.4 The American Psychological Association Election --
10.5 Simulation Results -- 10.6 Conclusions and Summary -- 10.7 Acknowledgements -- 10.8 References -- 11 Permutations and Regression Models -- 11.1 Introduction -- 11.2 Models for Random Permutations -- 11.3 Sufficient Statistics and
Log-linear Models -- 11.4 Conclusions -- 11.5 References -- 12 Aggregation Theorems and the Combination of Probabilistic Rank Orders -- 12.1 Introduction -- 12.2 Notation and Basic Aggregation Theorems -- 12.3 Specific Multidimensional
Ranking and Subset Selection Models and Their Properties -- 12.4 Multidimensional Random Variable Models -- 12.5 Conclusion -- 12.6 References -- 13 A Nonparametric Distance Model for Unidimensional Unfolding -- 13.1 Introduction --
13.2 Social Choice Theory -- 13.3 Distance Measures for Rankings -- 13.4 Strongly Unimodal Distance Models for Rankings -- 13.5 Generalization of Coombs’ and Goodman’s Conditions -- 13.6 Equal Results for ML or MNI Criterion -- 13.7
Unfolding and Social Choice Theory: Illustrations -- 13.8 Discussion -- 13.9 References -- Miscellanea -- Models on Spheres and Models for Permutations -- Complete Consensus and Order Independence: Relating Ranking and Choice --
Ranking From Paired Comparisons by Minimizing Inconsistency -- Graphical Techniques for Ranked Data -- Matched Pairs and Ranked Data
ISBN:9781461227380
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Series:Lecture Notes in Statistics: 80
Keywords: Mathematics , Probabilities , Mathematics , Probability Theory and Stochastic Processes
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Call number:SPRINGER-1983-9781489921512:ONLINE Show nearby items on shelf
Title:Human Assessment and Cultural Factors
Author(s):
Date:1983
Size:1 online resource (671 p.)
Note:10.1007/978-1-4899-2151-2
Contents:Section I. Human Assessment Worldwide -- 1. Recent Issues in Educational Selection in the Third World -- 2. Human Assessment in the Indian Context -- 3. Large-Scale Assessment of Educational Aptitude in Nigeria -- 4. Testing in Africa
and America: The Search for Routes -- 5. The Assessment of Psychological Abilities and Psychologists’ Inabilities in the South Pacific -- 6. Are Western Psychological Concepts Valid in Africa? A Nigerian Review -- 7. Human Assessment —
The Work of the Scottish Council for Research in Education -- 8. The Progressive Matrices and Mill Hill Vocabulary Scale in Western Societies -- Section II. Contexts of Assessment -- 9. Textured Contexts: Systems and Situations in
Cross-Cultural Psychology -- 10. On the Search for the Independent Variable in Cross-Cultural Psychology -- 11. Dress Rehearsals for Psychological Performance -- 12. Context in the Assessment of Mathematical Concepts from Hunting
Societies -- 13. The Child and His Environment -- 14. Rediscovering “Rote”: Some Cognitive and Pedagogical Preliminaries -- 15. Psychological Differentiation in a Rural Yucatec Mayan Village -- Section III. Assessment Trends and Issues
-- 16. Studying Individual Differences in Cognitive Abilities: Implications for Cross-Cultural Studies -- 17. Psychometric Approaches to Intergroup Comparison: The Problem of Equivalence -- 18. Stalking the Wily Emic: Alternatives to
Cross-Cultural Measurement -- 19. The Structure, Organization and Correlates of Cognitive Speed and Accuracy -- 20. Conditional Item Bias Methods -- 21. Continuous Work Tests: Their Scope in Cross-Cultural Contexts -- 22. Measurement
of Spatial Abilities: Some Comments Prompted by Cross-Cultural Studies -- Section IV. Assessing Personality and Motivation -- 23. The Cross-Cultural Use of Personality Tests -- 24. A Dynamic Research Strategy for Universals in the
Motivation and Personality Domain -- 25. The Cross-Cultural Generalizability of Personality Construct Measures -- 26. Personality Measurement: Do the Scales Have Similar Meanings in Another Culture? -- 27. A Measurement Study of Test
Anxiety Emphasizing its Evaluative Context -- 28. Antecedents to Emotions Across Cultures -- 29. The Cross-Cultural Assessment of Coping Skills -- 30. Students’ Perception of What Causes Their Achievement in School -- 31. Comparisons
of Self-Concept Scores of Children in America and Taiwan -- Section V. Assessing Attitudes and Social Behaviour -- 32. The Cross-Cultural Assessment of Normative Concepts: Some Considerations of the Affinity between Methodological
Approaches and Preferred Theories -- 33. Assessment of Values and Attitudes in the Study of Fertility: Problems and Prospects -- 34. The Use of Ambiguous Photographic Stimuli in the Assessment of Attitudes to Children and Family Size
in South Asia -- 35. Issues in the Assessment of Attitudes in Pre- and Marginally-Literate Cultures -- 36. Attitudes and Action: The Problem of Child Abuse in Kenya -- 37. The Benefits of Close Intercultural Relationships -- 38.
Assessing the Patterns and Experience of Viewing Television -- Section VI. Assessment in Organizations -- 39. Cross-Cultural Organizational Psychology: Challenges and Limitations -- 40. Estimating Causes of Ethnic Differences in the
Effects of Schooling -- 41. Cross-Cultural Testing within a Multicultural Society -- 42. Cognitive Style and Language Performance of Nigerian Secondary School Students -- 43. Assessment of Spoken English Language Problems of Non-Native
English Speakers -- 44. A Picture Vocabulary Test for the Eastern James Bay Cree -- 45. A Longitudinal Study in Predicting School Performances in Tanzania -- Author Index
ISBN:9781489921512
Series:eBooks
Series:SpringerLink (Online service)
Series:Springer eBooks
Series:NATO Conference Series, III Human Factors : 21
Keywords: Physics , Physics , Physics, general
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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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