A Comparison of Regression Calibration Approaches for Designs with Internal Validation Data

Details

• Personal Author:
  Hauser R ; Hernandez-Avila M ; Hu H ; Spiegelman D ; Thurston SW ; Williams PL
• Description:
  We compare the asymptotic relative efficiency of several regression calibration methods of correcting for measurement error in studies with internal validation data, when a single covariate is measured with error. The estimators we consider are appropriate in main study/hybrid validation study designs, where the latter study includes internal validation and may include external validation data. Although all of the methods we consider produce consistent estimates, the method proposed by Spiegelman et al. (Statistics in Medicine, 20 (2001) 139) has an asymptotically smaller variance than the other methods. The methods for measurement error correction are illustrated using a study of the effect of in utero lead exposure on infant birth weight. [Description provided by NIOSH]
• Subjects:
  Blood Environmental Exposure Epidemiology Lead Men Occupational Health Pregnancy Risk Assessment Risk Factors Safety Women Workplace

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• Keywords:
  Author Keywords: Bone Lead Children Errors-in-variables Exposure Levels Humans Internal Validation Study In Utero Exposure Measurement Equipment Measurement Error Models Prenatal Exposure Risk Factors Samplers Tissue Culture Work Environment Workers

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• ISSN:
  0378-3758
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Journal Article
• Place as Subject:
  Massachusetts ; New York ; OSHA Region 1 ; OSHA Region 2
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Pages in Document:
  175-190
• Volume:
  131
• Issue:
  1
• NIOSHTIC Number:
  nn:20059621
• Citation:
  J Stat Plann Inference 2005 Apr; 131(1):175-190
• Contact Point Address:
  Sally W. Thurston, Department of Biostatistics and Computational Biology, University of Rochester Medical Center, 601 Elmwood Avenue, P.O. Box 630, Rochester, NY 14642, USA
• Email:
  thurston@bst.rochester.edu
• CAS Registry Number:
  Lead (CAS RN 7439-92-1)
• Federal Fiscal Year:
  2005
• Performing Organization:
  Harvard University, Boston, MA
• Peer Reviewed:
  True
• Start Date:
  19960930
• Source Full Name:
  Journal of Statistical Planning and Inference
• End Date:
  20000929
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:8a3494bec203a0a3319432a337a90caf86e0a339f60be69d9da9b32f3ee12962c1dc0285a5c6ac96ffaa405120e57dba81a3011dcb032de2851429298616dd37
• Download URL:
  https://stacks.cdc.gov/view/cdc/223779/cdc_223779_DS1.pdf
• File Type:
  [PDF - 383.18 KB ]