What techniques can social scientists use when an outcome variable for a sample (for example, y) is not representative of the population for which generalized results are preferred? Author Richard Breen provides an introduction to regression models for such data, including censored, sample-selected, and truncated data. Regression Models begins with a discussion of the Tobit model and examines issues such as maximum likelihood estimation and the interpretation of parameters. The author next discusses the basic sample selection model and the truncated regression model. Elaborating on the modeling of censored and sample-selected data via maximum likelihood, he shows the close links between the models introduced and other regression models for non-continuous dependent variables, such as the ordered probit. Concluding with an exploration of some of the criticisms of these approaches and difficulties associated with them, this volume gives readers a guide to the practical utility of these models.

About the Author
I am an Official Fellow of Nuffield College, Oxford. Between 1997 and 2001 I was Professor of Sociology at the European University Institute, Florence, where my Chair was called ' Social Stratification and Inequality'. Before going to Florence I was Professor of Sociology at Queen's University, Belfast, and, before that, I worked at the Economic and Social Research Institute in Dublin. I am a Fellow of the British Academy, a Member of the Royal Irish Academy and a member of Academia Europaea. I serve as a member of the Scientific Committee of the Centro de Estudios Avanzados en Ciencias Sociales, Juan March Institute, Madrid and on the Scientific Advisory Board of the Mannheimer Zentrum fur Europaische Sozialforschung. My research interests are social stratification and inequality, and the application of formal models in the social sciences.


Book Information
ISBN 9780803957107
Author Richard Breen
Format Paperback
Page Count 88
Imprint SAGE Publications Inc
Publisher SAGE Publications Inc
Weight(grams) 110g