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1. R for SAS and SPSS Users
by Robert A. Muenchen
出版情報: New York, NY : Springer Science+Business Media, LLC, 2011
シリーズ名: Statistics and Computing ;
オンライン: http://dx.doi.org/10.1007/978-1-4614-0685-3
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2. Multidimensional Item Response Theory
by M.D. Reckase
出版情報: New York, NY : Springer-Verlag New York, 2009
シリーズ名: Statistics for Social and Behavioral Sciences ;
オンライン: http://dx.doi.org/10.1007/978-0-387-89976-3
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3. R for SAS and SPSS Users
by Bob München
出版情報: New York, NY : Springer-Verlag New York, 2009
シリーズ名: Statistics and Computing ;
オンライン: http://dx.doi.org/10.1007/978-0-387-09418-2
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4. Quantitative Psychology Research : The 78th Annual Meeting of the Psychometric Society
edited by Roger E. Millsap, Daniel M. Bolt, L. Andries van der Ark, Wen-Chung Wang
出版情報: Cham : Springer International Publishing : Imprint: Springer, 2015
シリーズ名: Springer Proceedings in Mathematics & Statistics ; 89
オンライン: http://dx.doi.org/10.1007/978-3-319-07503-7
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目次情報: 続きを見る
An empirical assessment of Guttman’s Lambda 4 reliability coefficient
Partitioning variance into constituents in multiple regression models: Commonality analysis
Thurstonian item response theory and an application to attitude items
Mediation analysis for ordinal outcome variables
MTP2 and partial correlations in monotone higher-order factor models
An option-based partial credit item response model
What do you mean by a difficult item, On the interpretation of the difficulty parameter in a Rasch model
Vertical comparison using reference sets
An empirical assessment of Guttman’s Lambda 4 reliability coefficient
Partitioning variance into constituents in multiple regression models: Commonality analysis
Thurstonian item response theory and an application to attitude items
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5. Quantitative Psychology Research : The 79th Annual Meeting of the Psychometric Society, Madison, Wisconsin, 2014
edited by L. Andries van der Ark, Daniel M. Bolt, Wen-Chung Wang, Jeffrey A. Douglas, Sy-Miin Chow
出版情報: Cham : Springer International Publishing : Imprint: Springer, 2015
シリーズ名: Springer Proceedings in Mathematics & Statistics ; 140
オンライン: http://dx.doi.org/10.1007/978-3-319-19977-1
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Item Response Theory
Test Data
Factor Analysis
Structural Equation Modeling
Cognitive Diagnostic Modeling
Propensity Scores
Multilevel Modeling
Mediation Analysis
Time Series
Item Response Theory
Test Data
Factor Analysis
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6. Multivariate and Mixture Distribution Rasch Models : Extensions and Applications
by Matthias Davier ; edited by Claus H. Carstensen
出版情報: New York, NY : Springer Science + Business Media, LLC, 2007
シリーズ名: Statistics for Social and Behavioral Sciences ;
オンライン: http://dx.doi.org/10.1007/978-0-387-49839-3
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7. Linking and Aligning Scores and Scales
edited by Neil J. Dorans, Mary Pommerich, Paul W. Holland
出版情報: New York, NY : Springer, 2007
シリーズ名: Statistics for Social and Behavioral Sciences ;
オンライン: http://dx.doi.org/10.1007/978-0-387-49771-6
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8. Design of Observational Studies
by Paul R. Rosenbaum
出版情報: New York, NY : Springer-Verlag New York, 2010
シリーズ名: Springer Series in Statistics ;
オンライン: http://dx.doi.org/10.1007/978-1-4419-1213-8
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9. Quantitative Psychology : 84th Annual Meeting of the Psychometric Society, Santiago, Chile, 2019. 1st ed. 2020
edited by Marie Wiberg, Dylan Molenaar, Jorge González, Ulf Böckenholt, Jee-Seon Kim
出版情報: Cham : Springer International Publishing : Imprint: Springer, 2020
シリーズ名: Springer Proceedings in Mathematics & Statistics ; 322
オンライン: https://doi.org/10.1007/978-3-030-43469-4
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目次情報: 続きを見る
Chapter 1: Stories Of Successful Careers In Psychometrics And What We Can Learn From Them
Chapter 2: Developing A Concept Map For Rasch Measurement Theory
Chapter 3: Person Parameter Estimation For IRT Models Of Forced-Choice Data: Merits And Perils Of Pseudo-Likelihood Approaches
Chapter 4: An Extended Item Response Tree Model For Wording Effects In Mixed-Format Scales
Chapter 5: The Four-Parameter Normal Ogive Model With Response Time
Chapter 6: A Bayesian Graphical And Probabilistic Proposal For Bias Analysis
Chapter 7: Comparing Hyperprior Distributions To Estimate Variance Components For Interrater Reliability Coefficients
Chapter 8: A Hierarchical Joint Model For Bounded Response Time And Response Accuracy
Chapter 9: Selecting A Presmoothing Model In Kernel Equating
Chapter 10: Practical Implementation Of Test Equating Using R
Chapter 11: Predictive Validity Under Partial Observability
Chapter 12: Multiple-Group Propensity Score Inverse Weights Trimming And Its Impact On Covariate Balance And On Bias In Treatment Effect Estimation
Chapter 13: Procrustes Penalty Function For Matching Matrices To Targets With Its Applications
Chapter 14: Factor Score Estimation From The Perspective Of Item Response Theory
Chapter 15: On The Precision Matrix In The Semi-High Dimensional Settings
Chapter 16: The Performance Of The Modified Continuous A-Stratification Indices In Computerized Adaptive Testing
Chapter 17: Constant CSEM Achieved Through Scale Transformation And Adaptive Testing
Chapter 18: Synergized Bootstrapping: The Whole Is Faster Than The Sum Of Its Parts
Chapter 19: Synchronized Time Profile With Applications To Nearest Neighbor Classification
Chapter 20: Topic Modeling Of Constructed-Response Answers On Social Study Assessments
Chapter 21: Impact Of Measurement Bias On Diagnostic Clinical Measures
Chapter 22: Reliability And Structure Validity Of A Teacher Pedagogical Competencies Scale: A Case Study From Chile
Chapter 23: Psychoperiscope
Chapter 24: Modeling Household Food Insecurity With A Polytomous Rasch Model
Chapter 25: Classical Perspectives Of Controlling Acquiescence With Balanced Scales
Chapter 26: Testing Heterogeneity In Inter-Rater Reliability
Chapter 27: An Application Of Regularized Extended Redundancy Analysis Via Generalized Redundancy Analysis Via Generalized Estimating Equations To The Study Of Co-Occurring Substance Use Among US Adults
Chapter 28: Permutation Test Of Regression Coefficients In Social Network Data Analysis
Index
Chapter 1: Stories Of Successful Careers In Psychometrics And What We Can Learn From Them
Chapter 2: Developing A Concept Map For Rasch Measurement Theory
Chapter 3: Person Parameter Estimation For IRT Models Of Forced-Choice Data: Merits And Perils Of Pseudo-Likelihood Approaches
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10. Applied Multiple Imputation : Advantages, Pitfalls, New Developments and Applications in R. 1st ed. 2020
by Kristian Kleinke, Jost Reinecke, Daniel Salfrán, Martin Spiess
出版情報: Cham : Springer International Publishing : Imprint: Springer, 2020
シリーズ名: Statistics for Social and Behavioral Sciences ;
オンライン: https://doi.org/10.1007/978-3-030-38164-6
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目次情報: 続きを見る
1 Introduction and Basic Concepts
2 Missing Data Mechanism and Ignorability
3 Missing Data Methods
4 Multiple Imputation: Theory
5 Multiple Imputation: Application
6 Multiple Imputation: New Developments
A Appendices
Index
1 Introduction and Basic Concepts
2 Missing Data Mechanism and Ignorability
3 Missing Data Methods