Beschreibung
Since Charles Spearman published his seminal paper on factor analysis in 1904 and Karl Joresk ¨ og replaced the observed variables in an econometric structural equation model by latent factors in 1970, causal modelling by means of latent variables has become the standard in the social and behavioural sciences. Indeed, the central va- ables that social and behavioural theories deal with, can hardly ever be identi?ed as observed variables. Statistical modelling has to take account of measurement - rors and invalidities in the observed variables and so address the underlying latent variables. Moreover, during the past decades it has been widely agreed on that serious causal modelling should be based on longitudinal data. It is especially in the ?eld of longitudinal research and analysis, including panel research, that progress has been made in recent years. Many comprehensive panel data sets as, for example, on human development and voting behaviour have become available for analysis. The number of publications based on longitudinal data has increased immensely. Papers with causal claims based on cross-sectional data only experience rejection just for that reason.
Produktsicherheitsverordnung
Hersteller:
Springer Verlag GmbH
juergen.hartmann@springer.com
Tiergartenstr. 17
DE 69121 Heidelberg
Inhalt
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: Multivariate and 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 Marc J.M.H. Delsing: Continuous Time Modeling of Panel Data by means of SEM.- John J. 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 Heterogeneity in Event History Analysis.
