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Analysis of case-cohort data: a comparison of different methods
N Charlotte Onland-Moret1, Daphne L van der A, Yvonne T van der Schouw
1Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Room Str. 6.131, PO Box 85500, 3508 GA Utrecht, The Netherlands.
Journal of Clinical Epidemiology
|March 10, 2007
Summary
The case-cohort design is efficient for epidemiological studies. Prentice's method closely matched full-cohort estimates, especially in smaller cohorts or with smaller subcohort sizes, ensuring reliable results.
Area of Science:
- Epidemiology
- Biostatistics
Background:
- The case-cohort design offers a balance between the efficiency of case-control studies and the robustness of prospective cohort studies.
- Standard Cox proportional-hazards models require adaptation for case-cohort data due to sampling complexities.
Purpose of the Study:
- To compare the performance of three proposed weighting methods (Prentice's, Barlow's, Self and Prentice's) for Cox models in case-cohort studies.
- To identify the most reliable method for estimating effects in case-cohort designs under various sampling fractions and cohort sizes.
Main Methods:
- A case-cohort study was conducted on 17,357 women, examining the association between body mass index and cardiovascular disease.
- Analyses involved varying subcohort sizes (sampling fractions from 0.005 to 0.15) and simulations were used to assess method performance under different conditions.
Main Results:
- All three methods yielded identical estimates and standard errors (SE) even with a sampling fraction as low as 0.01.
- Results from case-cohort analyses closely aligned with full-cohort analyses when sampling fractions were 0.10 or higher.
- Discrepancies among methods emerged in smaller full cohorts (<1,250 subjects) or when subcohort sizes were less than 15%.
Conclusions:
- Prentice's method demonstrated effect estimates and SE that most closely approximated those from full-cohort analyses in challenging scenarios.
- The findings highlight the importance of method selection in case-cohort studies, particularly when dealing with limited sample sizes or small subcohorts.
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