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Analytic methods for two‐stage case‐control studies and other stratified designs
Author(s) -
Flanders W. Dana,
Greenland Sander
Publication year - 1991
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.4780100509
Subject(s) - covariate , statistics , stage (stratigraphy) , missing data , control (management) , econometrics , computer science , mathematics , artificial intelligence , paleontology , biology
Nested case‐control studies, or case‐control studies within a cohort, combine the advantages of cohort studies with the efficiency of case‐control studies. Case‐control studies can often be viewed as having two stages; the first stage consists of vital status, disease, and basic covariate ascertainment, and the second stage consists of detailed covariate and exposure ascertainment. Breslow and Cain (1988) and Breslow and Zhao (1988) recently showed that conventional analyses of such two‐stage studies may ignore some of the available information. In this paper, we show how one can adapt the pseudo‐likelihood analyses developed by Kalbfleisch and Lawless (1988) to the analysis of data from two‐stage case‐control studies.