Overview

The book provides a simple, intuitive introduction to regression models for qualitative and discrete dependent variables, to sample selection models, and to event history models, all in the context of maximum likelihood estimation. It presents a wide range of commonly used models. The book thereby enables the reader to become a critical consumer of current empirical social science research and to conduct own empirical analyses. The book includes numerous examples, illustrations, and exercises. It can be used as a textbook for an advanced undergraduate, a Master's or a first-year Ph.D. course in microdata analysis, and as a reference for practitioners and researchers.

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9783540927495

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Reviews

From the reviews: <p> The book deals with the analysis of microdata where the usual conditional expectation functions (CEF) modeling is changed towards conditional probability functions (CPF). a ] Numerous illustrations and numerical examples from the area of social sciences are declineated to show the utility and methodology of fitting a variety of models. This book provides subject matters different from routine books a ] . The book will definitely enhance the knowledge of students and equip the researchers for proper analysis and reliable results. (B. L. Agarwal, Zentralblatt MATH, Vol. 1100 (2), 2007) <p> Analysis of Microdata is comprised of eight chapters, which can be thought of as falling into two parts. a ] At the time of writing this review I have just finished teaching a microeconometrics course using this book as the primary text. I found that it worked very well. Not only is the material well chosen but I thought it very well exposited. a ] I cannot give any textbook a more ringing endorsement than that. (Christopher L. Skeels, Economic Record, March, 2007)

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