Maximum Likelihood Fitting of General Risk Models to Stratified Data

Barry E. Storer, Sholom Wacholder and Norman E. Breslow

Journal of the Royal Statistical Society Series C, 1983, vol. 32, issue 2, 172-181

Abstract: A recursive algorithm (Howard, 1972; Gail et al., 1981) useful for maximum conditional likelihood fitting of logistic regression models with large strata can be generalized to arbitrary relative risk models. An example is presented which permits comparison between fitting methods vis a vis stratified vs. unstratified analysis, additive vs. multiplicative risk model, and use of expected vs. observed information. On the basis of results from this comparison we suggest that Wald's test and the score test computed with observed information be avoided in non‐standard models. An interactive computer program is available for fitting multiplicative, additive and general risk models to stratified data.

Date: 1983
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