Social Science

Longitudinal and Panel Data: Analysis and Applications for the Social Sciences

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This text focuses on models and data that arise from repeated measurements taken from a cross-section of subjects. These models and data have found substantive applications in many disciplines within the biological and social sciences. The breadth and scope of applications appears to be increasing over time. However, this widespread interest has spawned a hodge- podge of terms; many different terms are used to describe the same concept. To illustrate, even the subject title takes on different meanings in different literatures; sometimes this topic is referred to as “longitudinal data” and sometimes as “panel data.” To welcome readers from a variety of disciplines, I use the cumbersome yet more inclusive descriptor “longitudinal and panel data.” This text is primarily oriented to applications in the social sciences. Thus, the data sets considered here are from different areas of social science including business, economics, education and sociology. The methods introduced into text are oriented towards handling observational data, in contrast to data arising from experimental situations, that are the norm in the biological sciences. Even with this social science orientation, one of my goals in writing this text is to introduce methodology that has been developed in the statistical and biological sciences, as well as the social sciences. That is, important methodological contributions have been made in each of these areas; my goal is to synthesize the results that are important for analyzing social science data, regardless of their origins. Because many terms and notations that appear in this book are also found in the biological sciences (where panel data analysis is known as longitudinal data analysis), this book may also appeal to researchers interested in the biological sciences. Despite its forty-year history and widespread usage, a survey of the literature shows that the quality of applications is uneven. Perhaps this is because longitudinal and panel data analysis has developed in separate fields of inquiry; what is widely known and accepted in one field is given little prominence in a related field. To provide a treatment that is accessible to researchers from a variety of disciplines, this text introduces the subject using relatively sophisticated quantitative tools, including regression and linear model theory. Knowledge of calculus, as well as matrix algebra, is also assumed. For Chapter 8 on dynamic models, a time series course would also be useful.

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: ., 2004

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1-364

Language

English

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NONE

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Subject(s)

Longitudinal and Panel Data: Analysis and Applica

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