Causal analysis with panel data
著者
書誌事項
Causal analysis with panel data
（Sage university papers series, . Quantitative applications in the social sciences ; no. 07-105）
Sage, c1995
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注記
Includes bibliographical references (p. 93-96)
内容説明・目次
内容説明
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.
目次
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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