Applied Panel Data Analysis for Economic and Social Surveys - Hardcover

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Hans-Jürgen Andreß a is Full Professor in Empirical Social and Economic Research at the Faculty of Business Administration, Economics and Social Sciences at the University of Cologne. His research interests include statistics and multivariate methods; labor market research; social and family policy.

Katrin Golsch is a senior researcher at the Department of Sociology at Bielefeld University, Germany. Her core interests include statistical methods for the analysis of survey data and longitudinal data analysis in particular, life-course analysis, social structure, labor market research and comparative sociological research.

Alexander Schmidt is a PhD candidate at the Research Training Group SOCLIFE, funded by the Germany Science Foundation. He teaches computer assisted data analysis and survey research at the Chair of Empirical Social and Economic Research at the Faculty of Business Administration, Economics and Social Sciences at the University of Cologne. His research focuses on social mobility and comparative welfare state analysis.

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Many economic and social surveys are designed as panel studies, which provide important data for describing social changes and testing causal relations between social phenomena. This textbook shows how to manage, describe, and model these kinds of data. It presents models for continuous and categorical dependent variables, focusing either on the level of these variables at different points in time or on their change over time. It covers fixed and random effects models, models for change scores and event history models. All statistical methods are explained in an application-centered style using research examples from scholarly journals, which can be replicated by the reader through data provided on the accompanying website. As all models are compared to each other, it provides valuable assistance with choosing the right model in applied research. The textbook is directed at master and doctoral students as well as applied researchers in the social sciences, psychology, business administration and economics. Readers should be familiar with linear regression and have a good understanding of ordinary least squares estimation.