Generalized Linear Models

Scott Pardo ()
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Scott Pardo: Ascensia Diabetes Care, Global Medical & Clinical Affairs

Chapter Chapter 9 in Statistical Analysis of Empirical Data, 2020, pp 93-106 from Springer

Abstract: Abstract Linear regression is based on the premise that the model is linear in parameters; a set of methods called “generalized linear models” relies on transformations of models that make them linear in parameters; however, the solution to estimation equations is often dependent on numerical approximations; Some more common and important generalized linear models are presented.

Keywords: Odds ratio; Logistic equation; Deviance; Maximum likelihood; Logistic regression; Poisson regression; Zero-inflated; Overdispersion (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-43328-4_9

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DOI: 10.1007/978-3-030-43328-4_9

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