On power and sample size calculations for likelihood ratio tests in generalized linear models.
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.
Shieh
G
G
Department of Management Science, National Chiao Tung University, Hsinchu, Taiwan 30050, Republic of China. gwshieh@cc.nctu.edu.tw
D001699:Biometry / Q000379:methods*; D016009:Chi-Square Distribution; D003198:Computer Simulation; D006801:Humans; D016013:Likelihood Functions; D015233:Models, Statistical; D009010:Monte Carlo Method; D011336:Probability; D012044:Regression Analysis; D015203:Reproducibility of Results; D018401:Sample Size; D012984:Software