R in Action, Second Edition: Data analysis and graphics with R by Robert Kabacoff

Author:Robert Kabacoff
Language: eng
Format: epub
Publisher: Manning Publications

Generalized linear models extend the linear-model framework to include dependent variables that are decidedly non-normal.

In this chapter, we’ll start with a brief overview of generalized linear models and the glm() function used to estimate them. Then we’ll focus on two popular models in this framework: logistic regression (where the dependent variable is categorical) and Poisson regression (where the dependent variable is a count variable).

To motivate the discussion, you’ll apply generalized linear models to two research questions that aren’t easily addressed with standard linear models:

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