Item request has been placed! ×
Item request cannot be made. ×
loading  Processing Request

A case-cohort design for assessing covariate effects in longitudinal studies.

Item request has been placed! ×
Item request cannot be made. ×
loading   Processing Request
اقرأ على الانترنت اقرأ أكثر حفظ في قائمتي
  • معلومة اضافية
    • المصدر:
      Publisher: Oxford University Press Country of Publication: United States NLM ID: 0370625 Publication Model: Print Cited Medium: Print ISSN: 0006-341X (Print) Linking ISSN: 0006341X NLM ISO Abbreviation: Biometrics Subsets: MEDLINE
    • بيانات النشر:
      Publication: March 2024- : [Oxford] : Oxford University Press
      Original Publication: Alexandria Va : Biometric Society
    • الموضوع:
      Case-Control Studies* ; Cohort Studies* ; Data Interpretation, Statistical* ; Models, Statistical*; Animals ; Asthma/immunology ; Cats ; Child, Preschool ; Computer Simulation ; Endotoxins/immunology ; Humans ; Infant ; Infant, Newborn ; Monte Carlo Method
    • نبذة مختصرة :
      The case-cohort design for longitudinal data consists of a subcohort sampled at the beginning of the study that is followed repeatedly over time, and a case sample that is ascertained through the course of the study. Although some members in the subcohort may experience events over the study period, we refer to it as the "control-cohort." The case sample is a random sample of subjects not in the control-cohort, who have experienced at least one event during the study period. Different correlations among repeated observations on the same individual are accommodated by a two-level random-effects model. This design allows consistent estimation of all parameters estimable in a cohort design and is a cost-effective way to study the effects of covariates on repeated observations of relatively rare binary outcomes when exposure assessment is expensive. It is an extension of the case-cohort design (Prentice, 1986, Biometrika73, 1-11) and the bidirectional case-crossover design (Navidi, 1998, Biometrics54, 596-605). A simulation study compares the efficiency of the longitudinal case-cohort design to a full cohort analysis, and we find that in certain situations up to 90% efficiency can be obtained with half the sample size required for a full cohort analysis. A bootstrap method is presented that permits testing for intra-subject homogeneity in the presence of unidentifiable nuisance parameters in the two-level random-effects model. As an illustration we apply the design to data from an ongoing study of childhood asthma.
    • الرقم المعرف:
      0 (Endotoxins)
    • الموضوع:
      Date Created: 20060113 Date Completed: 20060307 Latest Revision: 20061115
    • الموضوع:
      20240628
    • الرقم المعرف:
      10.1111/j.1541-0420.2005.00364.x
    • الرقم المعرف:
      16401271