Longitudinal research with latent variables

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. The main purpose of the book is to give a state of the art explanation of longitudinal research methodology with latent variables and to show how this methodology is implemented inpractice with current state of art software and real datasets. INDICE: A. Hagenaars: Loglinear Latent Variable Models for Longitudinal Categorical Data.- Geert Verbeke, Geert Molenberghs, and Dimitris Rizopoulos: Random Effects Models for Longitudinal Data.- Nicholas T. Longford: Multivariateand Multilevel Longitudinal Analysis.- Jeroen K. Vermunt: Longitudinal Research Using Mixture Models.- Kenneth A. Bollen and Catherine Zimmer: An Overview of the Autoregressive Latent Trajectory (ALT) Model.- Jacques J.F. Commandeur,Siem Jan Koopman, and Kees van Montfort: State Space Methods for Latent Trajectory and Parameter Estimation by Maximum Likelihood.- Johan H.L. Oud and MarcJ.M.H. Delsing: Continuous Time Modeling of Panel Data by means of SEM.- JohnJ. McArdle and Kevin J. Grimm: Five steps in Latent Curve and Latent Change Score Modeling with Longitudinal Data.-Daniel J. Blake, Janet M. Box-Steffensmeier, and Byungwon Woo: Structural Interdependence and Unobserved Heterogeneityin Event History Analysis.

• ISBN: 978-3-642-11759-6
• Editorial: Springer
• Encuadernacion: Cartoné
• Páginas: 301
• Fecha Publicación: 26/04/2010
• Nº Volúmenes: 1
• Idioma: Inglés