Longitudinal Models in the Behavioral and Related Sciences

This volume reviews longitudinal models and analysis procedures for use in the behavioral and social sciences. Written by distinguished experts in the field, the book presents the most current approaches and theories, and the technical problems that may be encountered along the way. Readers will find new ideas about the use of longitudinal analysis in solving problems that arise due to the specific nature of the research design and the data available. Longitudinal Models in the Behavioral and Related Sciences opens with the latest theoretical developments. In particular, the book addresses situations that arise due to the categorical nature of the data, issues related to state space modeling, and potential problems that may arise from network analysis and/or growth-curve data. The focus of part two is on the application of longitudinal modeling in a variety of disciplines. The book features applications such as heterogeneity on the patterns of a firm's profit, on house prices, and on delinquent behavior; non-linearity in growth in assessing cognitive aging; measurement error issues in longitudinal research; and distance association for the analysis of change. Part two clearly demonstrates the caution that should be taken when applying longitudinal modeling as well as in the interpretation of the results. This new volume is ideal for advanced students and researchers in psychology, sociology, education, economics, management, medicine, and neuroscience.

This volume reviews longitudinal models and analysis procedures for use in the behavioral and social sciences. Written by distinguished experts in the field, the book presents the most current approaches and theories, and the technical problems that may be encountered along the way. Readers will find new ideas about the use of longitudinal analysis in solving problems that arise due to the specific nature of the research design and the data available. Longitudinal Models in the Behavioral and Related Sciences opens with the latest theoretical developments. In particular, the book addresses situations that arise due to the categorical nature of the data, issues related to state space modeling, and potential problems that may arise from network analysis and/or growth-curve data. The focus of part two is on the application of longitudinal modeling in a variety of disciplines. The book features applications such as heterogeneity on the patterns of a firm's profit, on house prices, and on delinquent behavior; non-linearity in growth in assessing cognitive aging; measurement error issues in longitudinal research; and distance association for the analysis of change. Part two clearly demonstrates the caution that should be taken when applying longitudinal modeling as well as in the interpretation of the results. This new volume is ideal for advanced students and researchers in psychology, sociology, education, economics, management, medicine, and neuroscience.