On power and sample size calculations for likelihood ratio tests in generalized linear models

Gwowen Shieh*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

40 Scopus citations

Abstract

A direct extension of the approach described in Self, Mauritsen, and Ohara (1992, Biometrics 48, 31-39) for power and sample size calculations in generalized linear models is presented. The major feature of the proposed approach is that the modification accommodates both a finite and an infinite number of covariate configurations. Furthermore, for the approximation of the noncentrality of the noncentral chi-square distribution for the likelihood ratio statistic, a simplification is provided that not only reduces substantial computation but also maintains the accuracy. Simulation studies are conducted to assess the accuracy for various model configurations and covariate distributions.

Original languageEnglish
Pages (from-to)1192-1196
Number of pages5
JournalBiometrics
Volume56
Issue number4
DOIs
StatePublished - Dec 2000

Keywords

  • Generalized linear models
  • Likelihood ratio test
  • Logistic regression
  • Noncentral chi-square
  • Poisson regression
  • Sample size
  • Score test
  • Statistical power

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