Conditional logistic analysis of case-control studies with complex sampling

Conditional logistic analysis of case-control studies with complex sampling.

Methods for the analysis of unmatched case-control data based on a finite population sampling model are developed. Under this model, and the prospective logistic model for disease probabilities, a likelihood for case-control data that accommodates very general sampling of controls is derived. This likelihood has the form of a weighted conditional logistic likelihood. The flexibility of the meth...

Penalized Logistic Regression in Case-Control Studies

Likelihood-based inference of odds ratios in logistic regression models is problematic for small samples. For example, maximum-likelihood estimators may be seriously biased or even non-existent due to separation. Firth proposed a penalized likelihood approach which avoids these problems. However, his approach is based on a prospective sampling design and its application to case-control data has...

analysis of reading comprehension needs of the students of paramedical studies: the case of the students of health information management (him)

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Simulation for estimating statistical power of conditional logistic regression analysis in matched case-control study

Sampling strategies in nested case-control studies.

A stratified version of nested case-control sampling which we call "countermatching" is presented. This design uses data available for all cohort members to obtain a sample for collecting additional information in a case-control substudy. Hitherto the only stratified sampling design for such studies has involved matching of controls to cases with respect to confounding variables. However, in so...