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Maximum Likelihood Fitting of General Risk Models to Stratified Data
Author(s) -
Storer Barry E.,
Wacholder Sholom,
Breslow Norman E.
Publication year - 1983
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.2307/2347296
Subject(s) - statistics , maximum likelihood , mathematics , econometrics
SUMMARY 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.