A tutorial on generalized linear models

Raymond H. Myers, Douglas Montgomery

Research output: Contribution to journalArticlepeer-review

126 Scopus citations


Situations in which the observations are not normally distributed arise frequently in the quality engineering field. The standard approach to the analysis of such responses is to transform the response into a new quantity that behaves more like a normal random variable. An alternative approach is to use an analysis procedure based on the generalized linear model (GLM), where a nonnormal error distribution and a function that links the predictor to the response may be specified. We present an introduction to the GLM, and show how such models may be fit. We present the GLM as an analog to the normal theory linear model. The usefulness of this approach is illustrated with examples.

Original languageEnglish (US)
Pages (from-to)274-291
Number of pages18
JournalJournal of Quality Technology
Issue number3
StatePublished - Jul 1997


  • Data Analysis
  • Design of Experiments
  • Generalized Linear Models
  • Least Squares
  • Maximum Likelihood
  • Regression

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering


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