Regression models : censored, sample-selected, or truncated data
Author(s)
Bibliographic Information
Regression models : censored, sample-selected, or truncated data
（Sage university papers series, . Quantitative applications in the social sciences ; no. 07-111）
Sage, c1996
- : pbk
Available at / 54 libraries
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Chiba Prefectural University of Health Sciences Makuhari Campus Library
: pbk301.6||Q1||11140006461
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Library, Institute of Developing Economies, Japan External Trade Organization図
: pbkT||311||R318465500
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Note
Bibliography: p. 76-79
Description and Table of Contents
Description
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.
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