Abstract
Preface Acknowledgments Section I: Scaling Chapter 1: Dual Scaling - Shizuhiko Nishisato Chapter 2: Multidimensional Scaling and Unfolding of Symmetric and Asymmetric Proximity Relations - Willem J. Heiser and Frank M.T.A. Busing Chapter 3: Principal Components Analysis With Nonlinear Optimal Scaling Transformations for Ordinal and Nominal Data - Jacqueline J. Muelman, Anita J. Van der Kooij, and Willem J. Heiser Section II: Testing and Measurement Chapter 4: Responsible Modeling of Measurement Data for Appropriate Inferences: Important Advances in Reliability and Validity Theory - Bruno D. Zumbo and Andre A. Rupp Chapter 5: Test Modeling - Ratna Nandakumar and Terry Ackerman Chapter 6: Differential Item Functioning Analysis: Detecting DIF Items and Testing DIF Hypotheses - Louis A. Roussos and William Stout Chapter 7: Understanding Computerized Adaptive Testing: from Robbins-Monro to Lord and Beyond - Hua-Hua Chang Section III: Models for Categorical Data Chapter 8: Trends in Categorical Data Analysis: New, Semi-New, and Recycled Ideas - David Rindskopf Chapter 9: Ordinal Regression Models - Valen E. Johnson and James H. Albert Chapter 10: Latent Class Models - Jay Magidson and Jeroen K. Vermunt Chapter 11: Discrete-Time Survival Analysis - John B. Willett and Judith D. Singer Section IV: Models for Multilevel Data Chapter 12: An Introduction to Growth Modeling - Donald Hedecker Chapter 13: Multilevel Models for School Effectiveness Research - Russell W. Rumberger and Gregory J. Palardy Chapter 14: The Use of Hierarchical Models in Analyzing Data from Experiments and Quasi-Experiments Conducted in Field Settings - Michael Seltzer Chapter 15: Meta-Analysis - Spyros Konstantopoulos and Larry V. Hedges Section V: Models for Latent Variables Chapter 16: Determining the Number of Factors in Exploratory and Confirmatory Factor Analysis - Rick H. Hoyle and Jamieson L. Duvall Chapter 17: Experimental, Quasi-Experimental, and Nonexperimental Design and Analysis with Latent Variables - Gregory R. Hancock Chapter 18: Applying Dynamic Factor Analysis in Behavioral and Social Science Research - John R. Nesselroade and Peter C. M. Molenaar Chapter 19: Latent Variable Analysis: Growth Mixture Modeling and Related Techniques for Longitudinal Data - Bengt Muthen Section VI: Foundational Issues Chapter 20: Probabalistic Modeling with Bayesian Networks - Richard E. Neapolitan and Scott Morris Chapter 21: The Null Ritual: What You Always Wanted to Know About Significance Testing but Were Afraid to Ask - Gerd Gigerenzer, Stefan Krauss, and Oliver Vitouch Chapter 22: On Exogeneity - David Kaplan Chapter 23: Objectivity in Science and Structural Equation Modeling - Stanley A. Mulaik Chapter 24: Causal Inference - Peter Spirtes, Richard Scheines, Clark Glymour, Thomas Richardson, and Christopher Meek Index
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