On the computation of likelihood ratio and score test based confidence intervals in generalized linear models.
Numerical procedures for calculating likelihood ratio test and score test based confidence intervals in generalized linear models are considered. Newton's method appears to have better convergence properties than the secant method in the likelihood ratio test case. However, the secant method may be easier to program for models with link functions that are not natural. Similarly, the secant method is easier to implement for the computation of score test based intervals. The practical implementation of the procedures in GLIM is illustrated.
Alho
J M
JM
Institute for Environmental Studies, University of Illinois, Urbana-Champaign 61801.
D016001:Confidence Intervals; D006801:Humans; D016013:Likelihood Functions; D016014:Linear Models; D008433:Mathematics