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Generalized case-cohort sampling
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DOI：10.1111/1467-9868.00313.png)
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Abstract
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A class of cohort sampling designs, including nested case-control, case-cohort and classical case-control designs involving survival data, is studied through a unified approach using Cox's proportional hazards model. By finding an optimal sample reuse method via local averaging, a closed form estimating function is obtained, leading directly to the estimators of the regression parameters that are relatively easy to compute and are more efficient than some commonly used estimators in case-cohort and nested case-control studies. A semiparametric efficient estimator can also be found with some further computation. In addition, the class of sampling designs in this study provides a variety of sampling options and relaxes the restrictions of sampling schemes that are currently available.
Keywords:
collocation
integral operator
missing data
partial likelihood
projection
pseudo-likelihood
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