Book — 1 online resource (xix, 286 pages) : illustrations
Preface. Measurement and Repeated Observations of Categorical Data: D. Andrich, Measurement Criteria for Choosing Among Models with Graded Responses. B.O. Muthn, Growth Modeling with Binary Responses. G. Arminger, Probit Models for the Analysis of Limited-Dependent Panel Data. Catastrophe Theory: H.L.J. van der Maas and P.C.M. Molenaar, Catastrophe Analysis of Discontinuous Development. P.C.M. Molenaar and P. Hartelman, Catastrophe Theory of Stage Transitions in Metrical and Discrete Stochastic Systems. Latent Class and Log-Linear Models: L.M. Collins, P.L. Fidler, and S.E. Wugalter, Some Practical Issues Related to Estimation of Latent Class and Latent Transition Parameters. T.D. Wickens, Contingency Tables and Between-Subject Variability. C.C. Clogg and W. Manning, Assessing Reliability of Categorical Measurements Using Latent Class Models. D. Rindskopf, Partitioning Chi-square: Something Old, Something New, Something Borrowed, but Nothing BLUE (Just ML). A. von Eye and C. Spiel, Nonstandard Log-Linear Models for Measuring Change in Categorical Variables. H.J. Khamis, Application of the Multigraph Representation of Hierarchical Log-Linear Models. Applications: M.J. Rovine and A. von Eye, Correlation and Categorization under a Matching Hypothesis. S.L. Hershberger, Residualized Categorical Phenotypes and Behavioral Genetic Modeling. Chapter References. Subject Index.
(source: Nielsen Book Data)
Categorical Variables in Developmental Research provides developmental researchers with the basic tools for understanding how to utilize categorical variables in their data analysis. Covering the measurement of individual differences in growth rates, the measurement of stage transitions, latent class and log-linear models, chi-square, and more, the book provides a means for developmental researchers to make use of categorical data. (source: Nielsen Book Data)