Methods for the Analyses of Case‐Cohort Studies

Case‐cohort and nested case‐control sampling methods have recently been introduced as a means of reducing cost in large cohort studies. The asymptotic distribution theory results for relative rate estimation based on Cox type partial or pseudolikelihoods for case‐cohort and nested case‐control studies have been accounted for. However, many researchers use (stratified) frequency table methods for a first or primary summarization of the most important evidence on exposure‐disease or dose‐response relationships, i.e. the classical Mantel‐Haenszel analyses, trend tests and tests for heterogeneity of relative rates. These can be followed by exponential failure time regression methods on grouped or individual data to model relationships between several factors and response. In this paper we present the adaptations needed to use these methods with case‐cohort designs, illustrating their use with data from a recent case‐cohort study on the relationship between diet, life‐style and cancer. We assume a very general setup allowing piecewise constant failure rates, possible recurrent events per individual, independent censoring and left truncation.