Table Of Content

Author/Title Index (Volume 22) Adams, Raymond J., Wilson, Mark, & Wu, Margaret. Multilevel Item Response Models: An Approach to Errors in Variables Regression, No. 1, p. 47 Berger, Martijn P. F. See Veerkamp, Wim J. J. Boik, Robert J. Analysis of Repeated Measures Under Second-Stage Sphericity: An Empirical Bayes Approach, No. 2, p. 155 Casella, George. See Cleary, Richard J. Chen, Wen-Hung, & Thissen, David. Local Dependence Indexes for Item Pairs Using Item Response Theory, No. 3, p. 265 Cleary, Richard J., & Casella, George. An Application of Gibbs Sampling to Estimation in Meta-Analysis: Accounting for Publication Bias, No. 2, p. 141 Dayton, C. Mitchell. See Lin, Ting Hsiang Elliott, Pamela R. See Kaplan, David Ferron, John. Moving Between Hierarchical Modeling Notations, No. 1, p. 119 Gan, Nianci. See Thomas, Neal Gelman, Andrew. Using Exams for Teaching Concepts in Probability and Statistics, No. 2, p. 237 Gross, Alan L. Interval Estimation of Bivariate Correlations With Missing Data on Both Variables: A Bayesian Approach, No. 4, p. 407 Hancock, Gregory R., & Klockars, Alan J. Finite Intersection Tests: A Paradigm for Optimizing Simultaneous and Sequential Inference, No. 3, p. 291 Huberty, Carl J. See Olejnik, Stephen Hunka, Steve, & Leighton, Jacqueline. Defining Johnson-Neyman Regions of Significance in the Three-Covariate ANCOVA Using Mathematica, No. 4, p. 361 Jansen, Margo G. H. The Rasch Model for Speed Tests and Some Extensions With Ap- plications to Incomplete Designs, No. 2, p. 125 Kaplan, David, & Elliott, Pamela R. A Model-Based Approach to Validating Education Indicators Using Multilevel Structural Equation Modeling, No. 3, p. 323 Keyes, Tim K., & Levy, Martin S. Analysis of Levene’s Test Under Design Imbalance, No. 2, p. 227 Klockars, Alan J. See Hancock, Gregory R. Leighton, Jacqueline. See Hunka, Steve Levy, Martin S. See Keyes, Tim K. Li, Heng, & Wainer, Howard. Toward a Coherent View of Reliability in Test Theory, No. 4, p. 478 Li, Jianmin. See Olejnik, Stephen Lin, Ting Hsiang, & Dayton, C. Mitchell. Model Selection Information Criteria for Non- 486 Author/Title Index (Volume 22) Adams, Raymond J., Wilson, Mark, & Wu, Margaret. Multilevel Item Response Models: An Approach to Errors in Variables Regression, No. 1, p. 47 Berger, Martijn P. F. See Veerkamp, Wim J. J. Boik, Robert J. Analysis of Repeated Measures Under Second-Stage Sphericity: An Empirical Bayes Approach, No. 2, p. 155 Casella, George. See Cleary, Richard J. Chen, Wen-Hung, & Thissen, David. Local Dependence Indexes for Item Pairs Using Item Response Theory, No. 3, p. 265 Cleary, Richard J., & Casella, George. An Application of Gibbs Sampling to Estimation in Meta-Analysis: Accounting for Publication Bias, No. 2, p. 141 Dayton, C. Mitchell. See Lin, Ting Hsiang Elliott, Pamela R. See Kaplan, David Ferron, John. Moving Between Hierarchical Modeling Notations, No. 1, p. 119 Gan, Nianci. See Thomas, Neal Gelman, Andrew. Using Exams for Teaching Concepts in Probability and Statistics, No. 2, p. 237 Gross, Alan L. Interval Estimation of Bivariate Correlations With Missing Data on Both Variables: A Bayesian Approach, No. 4, p. 407 Hancock, Gregory R., & Klockars, Alan J. Finite Intersection Tests: A Paradigm for Optimizing Simultaneous and Sequential Inference, No. 3, p. 291 Huberty, Carl J. See Olejnik, Stephen Hunka, Steve, & Leighton, Jacqueline. Defining Johnson-Neyman Regions of Significance in the Three-Covariate ANCOVA Using Mathematica, No. 4, p. 361 Jansen, Margo G. H. The Rasch Model for Speed Tests and Some Extensions With Ap- plications to Incomplete Designs, No. 2, p. 125 Kaplan, David, & Elliott, Pamela R. A Model-Based Approach to Validating Education Indicators Using Multilevel Structural Equation Modeling, No. 3, p. 323 Keyes, Tim K., & Levy, Martin S. Analysis of Levene’s Test Under Design Imbalance, No. 2, p. 227 Klockars, Alan J. See Hancock, Gregory R. Leighton, Jacqueline. See Hunka, Steve Levy, Martin S. See Keyes, Tim K. Li, Heng, & Wainer, Howard. Toward a Coherent View of Reliability in Test Theory, No. 4, p. 478 Li, Jianmin. See Olejnik, Stephen Lin, Ting Hsiang, & Dayton, C. Mitchell. Model Selection Information Criteria for Non- 486 Nested Latent Class Models, No. 3, p. 249 Marcus, Sue M. Using Omitted Variable Bias to Access Uncertainty in the Estimation of an AIDS Education Treatment Effect, No. 2, p. 193 Olejnik, Stephen, Li, Jianmin, Supattathum, Suchada, & Huberty, Carl J. Multiple Testing and Statistical Power With Modified Bonferroni Procedures, No. 4, p. 389 Rudas, Tamas, & Zwick, Rebecca. Estimating the Importance of Differential Item Func- tioning, No. 1, p. 31 Schumacker, Randall E. See Thompson, Kenneth N. Supattathum, Suchada. See Olejnik, Stephen Teunissen, Joop. See van der Heijden, Peter G. M. Thissen, David. See Chen, Wen-Hung Thomas, D. Roland. A Note on Huberty’s and Wisenbaker’s “Views of Variable Impor- tance,” No. 3, p. 309 Thomas, Neal, & Gan, Nianci. Generating Multiple Imputations for Matrix Sampling Data Analyzed With Item Response Models, No. 4, p. 425 Thompson, Kenneth N., & Schumacker, Randall E. An Evaluation of Rosenthal and Rubin's Binomial Effect Size Display, No. 1, p. 109 Thum, Yeow Meng. Hierarchical Linear Models for Multivariate Outcomes, No. 1, p. 77 van der Heijden, Peter G. M., Teunissen, Joop, & van Orlé, Charles. Multiple Correspon- dence Analysis as a Tool for Quantification or Classification of Career Data, No. 4, p. 447 van Orlé, Charles. See van der Heijden, Peter G. M. Veerkamp, Wim J. J., & Berger, Martijn P. F. Some New Item Selection Criteria for Adaptive Testing, No. 2, p. 203 Wainer, Howard. Improving Tabular Displays, With NAEP Tables as Examples and In- spirations, No. 1, p. | Wainer, Howard. See Li, Heng Wilson, Mark. See Adams, Raymond J. Wu, Margaret. See Adams, Raymond J. Zimmerman, Donald W. A Note on Interpretation of the Paired-Samples t Test, No. 3, p. 349 Zwick, Rebecca. See Rudas, Tamas Index of Book Reviews (Volume 22) Briefly Noted: Short Book Reviews by the Book Review Editor, by David Rindskopf, No. 2, p. 244 487 Keyword Index (Volume 22) Adaptive testing 2:203 Hierarchical linear models 1:77, 1:119 Analysis of variance 4:478 ANOVA 2:227 Johnson-Neyman ANCOVA 4:361 Armor’s theta 4:478 Incomplete data 2:125 Independent samples 3:349 Bayesian estimation 2:141 Individual differences 1:77 Bayesian statistics 4:407 Instruction 2:237 Binomial effect size display (BESD) IRT 3:265 1:109 Item response models 1:47 Bonferroni 3:291, 4:389 Item selection 2:203 Calibration 2:237 Latent class analysis 3:249 Career data 4:447 Leverage 2:227 Causal inference 2:193 Local dependence 3:265 Classification 4:447 Longitudinal data 4:447 Coefficient alpha 4:478 Coefficient of determination 1:109 MANOVA 2:155, 3:309 Correlated samples 3:349 Mantel-Haenszel test 1:31 Correlation 2:237 Matched pairs 3:349 Correlations 4:407 Mathematica 4:361 Correlation coefficient 1:109 Matrix sampling 4:425 Maximum likelihood estimation 1:31 Difference scores 3:349 Maximum likelihood 1:77 Differential item functioning 1:31 Measurement error 1:47, 4:425 Discriminant ratio coefficients 3:309 Missing data 4:407 Missing outcomes 1:77 Education indicators 3:323 Mixed linear models 1:119 Education policy 3:323 Mixture index of fit 1:31 Effect size 1:109 Model selection criteria 3:249 Efficiency 2:203 Multilevel data 1:77 EM algorithm 1:47, 4:425 Multilevel models 1:47 Empirical Bayes 1:77, 2:155 Multilevel modeling 3:323 Event history data 4:447 Multiple correspondence analysis 4:447 Expected mean squares 2:227 Multiple imputation 4:425 Multiple comparison procedures 3:291 Family wise error rate 4:389 Mulitple testing 4:389 Multivariate repeated measures 1:77 Gibbs sampling 2:141 Multivariate two-stage models 1:77 Graphical comprehension 1:1 Grouping variable effects 3:309 National Assessment of Educational Progress (NAEP) 1:1, 4:425 Heteroscedasticity 2:227 Nonhomogeneous regression 4:361 Hidden bias 2:193 Nonindependence 3:349 488 Observational study 2:193 Optimal test design 2:203 Paired samples 3:349 Phi coefficient 1:109 Power 2:227, 3:349 Prediction 2:237 Q, 3:265 Quasi-Newton 1:77 Random effects 1:77 Random effects models 2:141 Rasch model 2:125 Reading 2:125 Regression 2:237 Reliability 4:478 Repeated measures 2:155 Selection bias 2:141 Sensitivity 1:77 Sensitivity analysis 2:193 SIR algorithm 4:425 Spearman-Brown formula 4:478 Speed tests 2:125 Sphericity 2:155 Structural equation modeling 3:323 t prior 1:77 t test 3:349 Tabular displays 1:1 Type I error 3:349 Type II error 3:349 Unbalanced designs 2:227 Variable importance criteria 3:309