Advances in the statistical analysis of longitudinal data has been so rapid, that it has been difficult for empirically oriented social scientists to remain informed of all new developments in this important area of social methodology. This article offers some guidance on the use of various types of panel data analysis techniques, paying particular attention to the analysis of longitudinal panel data. The aim of this article is to describe in a succinct manner the logic underpinning a number of panel analysis techniques; outlining the types of inferences that can be drawn from employing specific techniques, and providing the reader with references to the literature associated with particular forms of panel data analysis. Five types of panel data analysis are discussed: Event history analysis, Sequential analysis, Hierarchical linear (or multi-level) modeling (with application to longitudinal data analysis), Structural equation modeling with longitudinal data, and use of Log- linear and Markov chain models for longitudinal data with categorical variables., Petr Pakosta, Petr Fučík., and Obsahuje bibliografii a bibliografické odkazy
Markéta Škodová v tomto čísle mluvila s Ing. Josefem Bečvářem o situaci ve výzkumu veřejného mínění v 60. a 70.letech, a také o jeho působení v Ústavu veřejného mínění. Ing. Josef Bečvář (* 1929) byl v letech 1967-1972 výzkumným pracovníkem Ústavu pro výzkum veřejného mínění Československé akademie věd. Předkládaný rozhovor s tímto sociologem je součástí kontinuální snahy CVVM o mapování různých aspektů dějin výzkumu veřejného mínění v České, resp. Československé republice., Markéta Škodová., and Seznam literatury
The aim of this article is to present a specific method for the study of the life-course, which focuses on life-course trajectories as a whole through the use of sequence analysis. In the first part, two approaches for the quantitative analysis of the life-course are distinguished: an event-oriented perspective and a trajectory-based (holistic) perspective. The holistic perspective is based on sequence analysis and more specifically on optimal matching. The trajectory-based perspective does not focus on single life events, but on whole sequences of events. In the second part, using the Czech wave of the ISSP 2002 dataset, which includes partnership and family histories, this article presents several examples of the use of sequence analysis of family trajectories. This study shows that sequence analysis can help identify patterns associated with typical and distinctive life-course trajectories., Jana Chaloupková., and Obsahuje bibliografii a bibliografické odkazy