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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.
The availability of microdata has increased rapidly over the last decades, and standard statistical and econometric software packages for data analysis include ever more sophisticated modeling options. The goal of this book, now initssecondedition,istofamiliarizethereaderwithawiderangeofcommonly used models, and thereby to enable her/him to become a critical consumer of current empirical research, and to properly conduct own empirical analyses. The book can be used as a textbook for an advanced undergraduate, a Master's or a ?rst-year Ph.D. course on the topic of microdata analysis. In economicsandrelateddisciplines,suchacourseistypicallyo?eredaftera?rst course on the linear regression model. Alternatively, the book can also serve as a supplementary text to applied ?eld courses, such as those dealing with empirical analyses in labor, health or education. Finally, it might provide a useful reference for graduate students, researchers and practitioners who encounter microdata in their work. The focus of the book is on regression-type models in the context of large cross-section samples where the dependent variable is qualitative or discrete, or where the sample is not randomly drawn from the population of interest, due to censoring or truncation of the dependent variable. While our ba- groundisineconomics,andweoccasionallyrefertoproblemsandapplications fromempiricaleconomics,themodelsdiscussedinthisbookshouldbeequally relevant wherever microdata are used, inside the social sciences, including for example quantitative political science and sociology, as well as outside.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
The availability of microdata has increased rapidly over the last decades, and standard statistical and econometric software packages for data analysis include ever more sophisticated modeling options. The goal of this book, now initssecondedition,istofamiliarizethereaderwithawiderangeofcommonly used models, and thereby to enable her/him to become a critical consumer of current empirical research, and to properly conduct own empirical analyses. The book can be used as a textbook for an advanced undergraduate, a Master's or a ?rst-year Ph.D. course on the topic of microdata analysis. In economicsandrelateddisciplines,suchacourseistypicallyo?eredaftera?rst course on the linear regression model. Alternatively, the book can also serve as a supplementary text to applied ?eld courses, such as those dealing with empirical analyses in labor, health or education. Finally, it might provide a useful reference for graduate students, researchers and practitioners who encounter microdata in their work. The focus of the book is on regression-type models in the context of large cross-section samples where the dependent variable is qualitative or discrete, or where the sample is not randomly drawn from the population of interest, due to censoring or truncation of the dependent variable. While our ba- groundisineconomics,andweoccasionallyrefertoproblemsandapplications fromempiricaleconomics,themodelsdiscussedinthisbookshouldbeequally relevant wherever microdata are used, inside the social sciences, including for example quantitative political science and sociology, as well as outside.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
From the reviews: "The book deals with the analysis of microdata where the usual conditional expectation functions (CEF) modeling is changed towards conditional probability functions (CPF). ... 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 ... . 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) "Analysis of Microdata is comprised of eight chapters, which can be thought of as falling into two parts. ... 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. ... I cannot give any textbook a more ringing endorsement than that." (Christopher L. Skeels, Economic Record, March, 2007)