On Power and Sample Size Calculations for Likelihood Ratio Tests in Generalized Linear Models
Summary. 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.