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Group Differences in Generalized Linear Models

  • Tim F. LiaoEmail author
Chapter
Part of the Handbooks of Sociology and Social Research book series (HSSR)

Abstract

This chapter deals with making comparisons between fixed groups in the framework of generalized linear models. First, we briefly introduce generalized linear models, the most common type of regression models. Next, we discuss a simple system for analyzing group differences in regression. We primarily focus on two types of comparisons—analyzing differences in the parameter vectors of the linear predictor and differences in the underlying distributions for the groups in the model. To illustrate such comparative methods for group differences, we perform analyses using real-world data. Theoretically, group differences in regression estimates can be viewed as an example of conditional causality. Practically, testing group differences in regression may see many useful applications in social science research.

Keywords

Generalize Linear Model Link Function Gamma Distribution Current Population Survey Exponential Family 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Department of SociologyUniversity of Illinois Urbana-ChampaignChampaignUSA

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