Compare the Marginal Effects for Environmental Exposure and Biomonitoring Data with Repeated Measurements and Values Below the Limit of Detection

Details

• Personal Author:
  Bertke SJ ; Chen I-C ; Estill, Cheryl F.
• Description:
  Background: Environmental exposure and biomonitoring data with repeated measurements from environmental and occupational studies are commonly right-skewed and in the presence of limits of detection (LOD). However, existing model has not been discussed for small-sample properties and highly skewed data with non-detects and repeated measurements. Objective: Marginal modeling provides an alternative to analyzing longitudinal and cluster data, in which the parameter interpretations are with respect to marginal or population-averaged means. Methods: We outlined the theories of three marginal models, i.e., generalized estimating equations (GEE), quadratic inference functions (QIF), and generalized method of moments (GMM). With these approaches, we proposed to incorporate the fill-in methods, including single and multiple value imputation techniques, such that any measurements less than the limit of detection are assigned values. Results: We demonstrated that the GEE method works well in terms of estimating the regression parameters in small sample sizes, while the QIF and GMM outperform in large-sample settings, as parameter estimates are consistent and have relatively smaller mean squared error. No specific fill-in method can be deemed superior as each has its own merits. [Description provided by NIOSH]
• Subjects:
  Environmental Exposure Epidemiology Occupational Health Safety
• Keywords:
  Analytical Models Author Keywords: Marginal Analysis Biomonitoring Environmental Exposure Left Censoring Limit Of Detection LOD Repeated Measures Right Skewness Statistical Quality Control
• ISSN:
  1559-0631
• Document Type:
  Text
• Genre:
  Journal Article
• Place as Subject:
  Chicago Region [OSHA] ; Ohio
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Division:
  DFSE - Division of Field Studies and Engineering
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  34
• Issue:
  6
• NIOSHTIC Number:
  nn:20069187
• Citation:
  J Expo Sci Environ Epidemiol 2024 Nov; 34(6):1018-1027
• Contact Point Address:
  I-Chen Chen, Division of Field Studies and Engineering, National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention, Cincinnati, OH, USA
• Email:
  okv0@cdc.gov
• Federal Fiscal Year:
  2025
• NORA Priority Area:
  Manufacturing
• Peer Reviewed:
  True
• Source Full Name:
  Journal of Exposure Science and Environmental Epidemiology
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:3111a49487c65893535fd9126e2bb15834d997375a1f621fb344f68fc312812c380fadeeb5a137e995ad344cfd2f2937dbbbdf996bd83aae3c5a66be571f8348
• Download URL:
  https://stacks.cdc.gov/view/cdc/207719/cdc_207719_DS1.pdf
• File Type:
  [PDF - 1.87 MB ]