Loglinear Latent Variable Models for Longitudinal Categorical Data -- Random Effects Models for Longitudinal Data -- Multivariate and Multilevel Longitudinal Analysis -- Longitudinal Research Using Mixture Models -- An Overview of the Autoregressive Latent Trajectory (ALT) Model -- State Space Methods for Latent Trajectory and Parameter Estimation by Maximum Likelihood -- Continuous Time Modeling of Panel Data by means of SEM -- Five Steps in Latent Curve and Latent Change Score Modeling with Longitudinal Data -- Structural Interdependence and Unobserved Heterogeneity in Event History Analysis.

This book combines longitudinal research and latent variable research, i.e. it explains how longitudinal studies with objectives formulated in terms of latent variables should be carried out, with an emphasis on detailing how the methods are applied. Because longitudinal research with latent variables currently utilizes different approaches with different histories, different types of research questions, and different computer programs to perform the analysis, the book is divided into nine chapters. Starting from (a) some background information about the specific approach (a short history and the main publications), each chapter then (b) describes the type of research questions the approach is able to answer, (c) provides statistical and mathematical explanations of the models used in the data analysis, (d) discusses the input and output of the programs used, and (e) provides one or more examples with typical data sets, allowing the readers to apply the programs themselves.