Does It Always Help to Adjust for Misclassification of a Binary Outcome in Logistic Regression

Details

• Personal Author:
  Carlin BP ; Gerberich, Susan G. ; Luan X ; Pan W
• Description:
  It is well known that in logistic regression, where the outcome is measured with error, a biased estimate of the association between the outcome and a risk factor may result if no proper adjustment is made. Hence, it seems tempting to always adjust for possible misclassification of the outcome. Here we show that it is not always beneficial to do so because, though the adjustment reduces the bias, it also inflates the variance, leading to a possibly larger mean squared error of the estimate. In the context of a data set on agricultural injuries, numerical evidence is provided through simulation studies. [Description provided by NIOSH]
• Subjects:
  Agriculture Occupational Health Quality Control Risk Assessment Risk Factors Safety
• Keywords:
  Agricultural-industry Analytical-methods Analytical-models Analytical-processes Author Keywords: Bias Injury-prevention Logistic Models Mathematical-models Mean Squared Error Measurement Error Qualitative-analysis Quality-standards Risk-analysis Risk-factors Sensitivity And Specificity Simulation Statistical-analysis Statistical-quality-control

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• ISSN:
  0277-6715
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Journal Article
• Place as Subject:
  Minnesota ; Nebraska ; OSHA Region 5 ; OSHA Region 7
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  24
• Issue:
  14
• NIOSHTIC Number:
  nn:20037631
• Citation:
  Stat Med 2005 Jul; 24(14):2221-2234
• Contact Point Address:
  Bradley P. Carlin, Division of Biostatistics, University of Minnesota, School of Public Health, Box 303 Mayo Memorial Building, 420 Delaware St., Minneapolis, MN 55455-0378, U.S.A
• Email:
  brad@biostat.umn.edu
• Federal Fiscal Year:
  2005
• Performing Organization:
  University of Minnesota Twin Cities
• Peer Reviewed:
  True
• Start Date:
  20050701
• Source Full Name:
  Statistics in Medicine
• End Date:
  20250630
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:f81b2e90109ddf91f7534fee5108059574d874d9d54b468cf6aa22809b6951839129833f57af9e766d5b01c71a834f8bf054b9fa2fdcc9a2cb91842076861c56
• Download URL:
  https://stacks.cdc.gov/view/cdc/188687/cdc_188687_DS1.pdf
• File Type:
  [PDF - 99.23 KB ]