title: Analysis of case-cohort data: a comparison of different methods.
abstract: OBJECTIVE
  The case-cohort design combines the advantages of a prospective cohort study and the efficiency of a case-control design. Usually a Cox proportional-hazards model is used for the analyses. However, adaptation of the model is necessary because of the sampling. We compared three methods that were proposed in the literature, which differ in weighting of study subjects: Prentice's, Barlow's, and Self and Prentice's method.
  
  
  METHODS
  In a cohort of 17,357 women we studied the relationship between body mass index and cardiovascular disease (n=821) with varying subcohort sizes (sampling fraction=0.005, 0.01, 0.05, 0.10, 0.15).
  
  
  RESULTS
  Even with a sampling fraction of 0.01, all three methods showed identical estimates and standard errors (SE). With sampling fractions >or=0.10, results of the case-cohort analyses were similar to the full-cohort analyses. With simulations, the three methods provided different results if the full cohort is small (<1,250 subjects, subcohort=10%, 8% failures) or if the subcohort size was smaller than 15% (full cohort of 1,000 observations, 8% failures). The difference between the methods did not change with the number of failures or with different effect sizes.
  
  
  CONCLUSIONS
  In the above-mentioned situations, the effect estimates and SE of Prentice's method most resembled the estimates of the full-cohort estimates.
authors.affiliation: Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Room Str. 6.131, PO Box 85500, 3508 GA Utrecht, The Netherlands.
authors.forename: N Charlotte
authors.initials: NC
authors.lastname: Onland-Moret
authors.forename: Daphne L
authors.initials: DL
authors.lastname: van der A
authors.forename: Yvonne T
authors.initials: YT
authors.lastname: van der Schouw
authors.forename: Wim
authors.initials: W
authors.lastname: Buschers
authors.forename: Sjoerd G
authors.initials: SG
authors.lastname: Elias
authors.forename: Carla H
authors.initials: CH
authors.lastname: van Gils
authors.forename: Jeroen
authors.initials: J
authors.lastname: Koerselman
authors.forename: Mark
authors.initials: M
authors.lastname: Roest
authors.forename: Diederick E
authors.initials: DE
authors.lastname: Grobbee
authors.forename: Petra H M
authors.initials: PH
authors.lastname: Peeters
mesh_terms: D000368:Aged; D000704:Analysis of Variance; D015992:Body Mass Index; D002318:Cardiovascular Diseases / Q000453:epidemiology*; D016022:Case-Control Studies; D015331:Cohort Studies; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D004812:Epidemiologic Methods; D005260:Female; D006801:Humans; D008875:Middle Aged; D009426:Netherlands / Q000453:epidemiology; D016016:Proportional Hazards Models; D011446:Prospective Studies; D018570:Risk Assessment / Q000379:methods