Abstract: This chapter provides a non-technical summary of the most salient features of generalized linear models for a single, univariate response. It presents a detailed and somewhat more technical overview of generalized linear models. Generalized linear models provide a unified method for analyzing diverse types of univariate responses. Generalized linear models are actually a broad class or collection of regression models, and they include as special cases the standard linear regression and analysis of variance models for a normally distributed continuous response, logistic regression models for a binary or dichotomous response, and log-linear or Poisson regression models for counts. The chapter focuses primarily on generalized linear models for binary and count data since, with the exception of continuous responses, these two data types are by far the most commonly encountered in applications. It deals with ordinal regression models because, when regarded as generalized linear models, the models have certain non-standard features.
Publication Year: 2011
Publication Date: 2011-08-10
Language: en
Type: other
Indexed In: ['crossref']
Access and Citation
Cited By Count: 2
AI Researcher Chatbot
Get quick answers to your questions about the article from our AI researcher chatbot