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Causal Analysis with Panel Data
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Causal Analysis with Panel Data



January 1995 | 104 pages | SAGE Publications, Inc

Panel data, which consist of information gathered from the same individuals or units at several different points in time, are commonly used in the social sciences to test theories of individual and social change. This book provides an overview of models that are appropriate for the analysis of panel data, focusing specifically on the area where panels offer major advantages over cross-sectional research designs: the analysis of causal interrelationships among variables. Without "painting" panel data as a cure all for the problems of causal inference in nonexperimental research, the author shows how panel data offer multiple ways of strengthening the causal inference process. In addition, he shows how to estimate models that contain a variety of lag specifications, reciprocal effects, and imperfectly measured variables. Appropriate for readers who are familiar with multiple regression analysis and causal modeling, this book will offer readers the highlights of developments in this technique from diverse disciplines to analytic traditions.


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Introduction
 
Modeling Change with Panel Data
 
Models with Reciprocal Causation
 
Measurement Error Models
 
Models of Spurious Association
 
Concluding Note on Causal Inference in Panel Analysis

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ISBN: 9780803938960
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