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link to cohort study, since this is also a type of cohort study. |
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==Example==
As an example, of the 91,523 women in the [[Nurses' Health Study]] who did not have cancer at baseline and who were followed for 14 years, 2,341 women had developed breast cancer by 1993. Several studies have used standard cohort analyses to study precursors to breast cancer, e.g. use of hormonal contraceptives,<ref name="pmid9051324">{{cite journal|author1=Hankinson SE |author2=Colditz GA |author3=Manson JE |author4=Willett WC |author5=Hunter DJ |author6=Stampfer MJ |display-authors=etal | title=A prospective study of oral contraceptive use and risk of breast cancer (Nurses' Health Study, United States). | journal=Cancer Causes Control | year= 1997 | volume= 8 | issue= 1 | pages= 65–72 | pmid=9051324 | doi= 10.1023/a:1018435205695|s2cid=24873830 | url=https://www.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&tool=sumsearch.org/cite&retmode=ref&cmd=prlinks&id=9051324 }}</ref> which is a covariate easily measured on all of the women in the cohort. However, note that in comparison to the cases, there are so many controls that each particular control contributes relatively little information to the analysis.
If, on the other hand, one is interested in the association between [[gene expression]] and breast cancer incidence, it would be very expensive and possibly wasteful of precious blood specimen to assay all 89,000 women without breast cancer. In this situation, one may choose to assay all of the cases, and also, for each case, select a certain number of women to assay from the risk set of participants who have not yet failed (i.e. those who have not developed breast cancer before the particular case in question has developed breast cancer). The risk set is often restricted to those participants who are matched to the case on variables such as age, which reduces the variability of effect estimates.
==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 than a full cohort analysis and more efficient than taking a simple random sample from the full cohort. 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 |
==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 |
==Case–cohort study==
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==Further reading==
*{{cite book |
{{Medical research studies}}
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