General Relative Rate Models for the Analysis of Studies Using Case-Cohort Designs

Details

• Personal Author:
  Kelly-Reif K ; Langholz B ; Richardson DB
• Description:
  A standard approach to analysis of case-cohort data involves fitting log-linear models. In this paper, we describe how standard statistical software can be used to fit a broad class of general relative rate models to case-cohort data and derive confidence intervals. We focus on a case-cohort design in which a roster has been assembled and events ascertained but additional information needs to be collected on explanatory variables. The additional information is ascertained just for persons who experience the event of interest and for a sample of the cohort members enumerated at study entry. One appeal of such a case-cohort design is that this sample of the cohort may be used to support analyses of several outcomes. The ability to fit general relative rate models to case-cohort data may allow an investigator to reduce model misspecification in exposure-response analyses, fit models in which some factors have effects that are additive and others multiplicative, and facilitate estimation of relative excess risk due to interaction. We address model fitting for simple random sampling study designs as well as stratified designs. Data on lung cancer among radon-exposed men (Colorado Plateau uranium miners, 1950-1990) are used to illustrate these methods. [Description provided by NIOSH]
• Subjects:
  Cohort Studies Epidemiology Lung Lung Diseases Neoplasms Occupational Health Respiratory System Respiratory Tract Diseases Safety Uranium
• Keywords:
  Author Keywords: Ccohort Studies Cohort Studies Cox Model Dose-response Function Lung Cancer Models Radiation Radon Statistical Statistical Analysis Statistical Software Uranium Miners

  More +
• ISSN:
  0002-9262
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Journal Article
• Place as Subject:
  California ; North Carolina ; OSHA Region 4 ; OSHA Region 9
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Pages in Document:
  444-450
• Volume:
  188
• Issue:
  2
• NIOSHTIC Number:
  nn:20057013
• Citation:
  Am J Epidemiol 2019 Feb; 188(2):444-450
• Contact Point Address:
  Dr. David B. Richardson, Department of Epidemiology, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599
• Email:
  david.richardson@unc.edu
• CAS Registry Number:
  Radon (CAS RN 10043-92-2)
• Federal Fiscal Year:
  2019
• Performing Organization:
  University of North Carolina, Chapel Hill
• Peer Reviewed:
  True
• Start Date:
  20150901
• Source Full Name:
  American Journal of Epidemiology
• End Date:
  20170831
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:fb590da5fd19ea59046b5eb48d1970fc28d800a4414d690991446245e877d28684a0ef02216ed514beb8ab2a97c1fa9c3b986d9c6481fa751e73c2c385641ff7
• Download URL:
  https://stacks.cdc.gov/view/cdc/214495/cdc_214495_DS1.pdf
• File Type:
  [PDF - 200.24 KB ]