Nested case–control study: Difference between revisions

Revision as of 18:03, 10 June 2017

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==Efficiency of the NCC model==

Commonly 1-4 controls are selected for each case. Since the covariate is not measured for all participants, the nested case control model is both less expensive and less efficient than a full-cohort analysis. However, it has been shown that with 4 controls per case and/or stratified sampling of controls, relatively little efficiency may be lost, depending on the method of estimation used .<ref name=Cai>{{cite journal |last=Cai |first=Tianxi |last2=Zheng |first2=Yingye |year=2012 |title=Evaluating prognostic accuracy of biomarkers in nested case–control studies |journal=Biostatistics |volume=13 |issue=1 |pages=89–100 |doi=10.1093/biostatistics/kxr021 }}</ref><ref>{{cite journal |last=Goldstein |first=Larry |last2=Zhang |first=Haimeng |year=2009 |title=Efficiency of the maximum partial likelihood estimator for nested case control sampling |journal=Bernoulli |volume=15 |issue=2 |pages=569–597 |jstor=20680165 }}</ref>

==Analysis of nested case-control studies==

The analysis of a nested case control model must take into account the way in which controls are sampled from the cohort. Failing to do so, such as by treating the cases and selected controls as the original cohort and performing a logistic regression, which is common, can result in biased estimates whose null distribution is different from what is assumed. Ways to account for the random sampling include [[conditional logistic regression]].,<ref>{{cite journal |last=Borgan |first=O. |last2=Goldstein |first2=L. |last3=Langholz |first3=B. |year=1995 |title=Methods for the Analysis of Sampled Cohort Data in the Cox Proportional Hazards Model |journal=[[Annals of Statistics]] |volume=23 |number=5 |pages=1749–1778 |jstor=2242544 }}</ref> and using [[inverse probability weighting]] to adjust for missing covariates among those who are not selected into the study.<ref name=Cai/>

==Case-cohort study==