Generalized linear models

Peter K Dunn

doi:10.1016/B978-0-12-818630-5.10077-6

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Generalized linear models

Peter K Dunn

International Encyclopedia of Education, 4th Edition, pp.583-589

Elsevier Science, 4th Edition

2023

DOI: https://doi.org/10.1016/B978-0-12-818630-5.10077-6

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Abstract

binomial

categorical data

gamma

hypothesis testing

linear models

normal

poisson

regression

statistics

univariate linear regression

Generalized linear models (GLMs) are extensions of linear regression models, and are useful for modeling response variables that do not follow a normal distribution. More specifically, GLMs are useful for modeling data that are proportions of a total, for modeling counts, and for modeling skewed continuous responses. GLMs are based on a unified, sound theory. GLMs can be fitted in all common statistical packages.

Details

Title: Generalized linear models
Authors: Peter K Dunn (Corresponding Author) - University of the Sunshine Coast, Queensland, School of Science, Technology and Engineering
Contributors: Robert J Tierney (Editor) - University of British Columbia
Fazal Rizvi (Editor) - University of Melbourne
Kadriye Erkican (Editor) - Educational Testing Service
Publication details: International Encyclopedia of Education, 4th Edition, pp.583-589
Publisher: Elsevier Science
Edition: 4th Edition
DOI: 10.1016/B978-0-12-818630-5.10077-6
Organisation Unit: School of Science, Technology and Engineering; University of the Sunshine Coast, Queensland
Language: English
Record Identifier: 99693198202621
Output Type: Encyclopedia entry

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