Cox regression analysis in presence of collinearity: an application to assessment of health risks associated with occupational radiation exposure

Details

• Personal Author:
  Kim MY ; Shore RE ; Xue X ; Kim MY ; Shore RE ; Xue X
• Description:
  This paper considers the analysis of time to event data in the presence of collinearity between covariates. In linear and logistic regression models, the ridge regression estimator has been applied as an alternative to the maximum likelihood estimator in the presence of collinearity. The advantage of the ridge regression estimator over the usual maximum likelihood estimator is that the former often has a smaller total mean square error and is thus more precise. In this paper, we generalized this approach for addressing collinearity to the Cox proportional hazards model. Simulation studies were conducted to evaluate the performance of the ridge regression estimator. Our approach was motivated by an occupational radiation study conducted at Oak Ridge National Laboratory to evaluate health risks associated with occupational radiation exposure in which the exposure tends to be correlated with possible confounders such as years of exposure and attained age. We applied the proposed methods to this study to evaluate the association of radiation exposure with all-cause mortality. [Description provided by NIOSH]
• Subjects:
  Age Factors Carcinogens Environmental Exposure Epidemiology Mass Behavior Men Occupational Exposure Occupational Health Radiation Risk Assessment Risk Factors Safety Women

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• Keywords:
  Age-factors Analytical-models Author Keywords: Ridge Regression Collinearity Cox Proportional Hazards Model Environmental-exposure Exposure-levels Exposure-limits Group-dynamics Humans Mathematical-models Models Molecular-biology Occupational Exposure Radiation-exposure Risk-factors Statistical-analysis

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• ISSN:
  1380-7870
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Journal Article ; Journal Article
• Place as Subject:
  New York ; OSHA Region 2
• CIO:
  National Institute for Occupational Safety and Health (NIOSH) ; National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health ; Workplace Safety & Health
• Location:
  North America ; North America
• Pages in Document:
  333-350
• Volume:
  13
• Issue:
  3
• NIOSHTIC Number:
  nn:20040338
• Citation:
  Lifetime Data Anal 2007 Sep; 13(3):333-350
• Contact Point Address:
  Xiaonan Xue, Division of Biostatistics, Department of Epidemiology & Population Health, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Belfer 1303C, Bronx, 10461, NY
• Email:
  xxue@aecom.yu.edu
• Federal Fiscal Year:
  2007
• Performing Organization:
  Albert Einstein College of Medicine
• Peer Reviewed:
  True
• Start Date:
  20040901
• Source Full Name:
  Lifetime Data Analysis
• End Date:
  20081231
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:1fbbd394029ba5ea5e83257c669579cfe5295252d085511ade6e41185073fa3a34a17019e2c6317ef45f471b0914cf8d25b9da7e6f0f7e3fff44612b6343d383
• Download URL:
  https://stacks.cdc.gov/view/cdc/193252/cdc_193252_DS1.pdf
• File Type:
  [PDF - 233.32 KB ]