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Marlod: An R Package to Model Environmental Exposure and Biomonitoring Data with Repeated Measurements and Values Below the Limit of Detection

Public Domain


Details

  • Personal Author:
    Chen I-C
  • Description:
    TO THE EDITOR: In environmental and occupational research, when concentration measurements are taken from the same individual or study site, they are considered to be repeated measurements. Furthermore, when these samples fall below the limit of detection (LOD) of laboratory instruments, they are referred to as left-censored repeated measures data. These unquantified measurements typically represent low-level concentrations between zero and the LOD. There is an increasing need for statistical models that can effectively analyze left-censored environmental exposure and biomonitoring data with repeated measures, particularly among industrial hygienists. This is due to the growing importance of estimating the impact of exposure on disease risk and understanding the variability in occupational exposure both within and between workers. Analytical results from laboratories, including data on environmental contaminants (e.g., from hand wipes or personal breathing zone air samples) and occupational exposures (e.g., from biological media such as urine or serum) are often subject to non-detectable concentrations and tend to exhibit right-skewed distributions. The statistical modeling of exposure data that contain both repeated samples and samples below the LOD can be complex. The author would like to introduce the R package 'marlod' to analyze left-censored repeated measures exposure data when: data are assumed to be log-normally distributed using marginal mean regression models that employ generalized estimating equations (GEE), generalized method of moments (GMM), and quadratic inference functions (QIF) estimation methods, data are not assumed to follow a specific distribution using marginal quantile regression models, and longitudinal data contain time-varying covariates. [Description provided by NIOSH]
  • Subjects:
  • Keywords:
  • ISSN:
    1559-0631
  • Document Type:
    Text
  • Genre:
    Journal Article
  • Place as Subject:
  • CIO:
    National Institute for Occupational Safety and Health (NIOSH)
  • Division:
    DFSE - Division of Field Studies and Engineering
  • Topic:
    Workplace Safety & Health
  • Location:
    North America
  • NIOSHTIC Number:
    nn:20070503
  • Citation:
    J Expo Sci Environ Epidemiol 2025 Jan; :[Epub ahead of print]
  • 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
  • Email:
    okv0@cdc.gov
  • Federal Fiscal Year:
    2025
  • Peer Reviewed:
    False
  • Source Full Name:
    Journal of Exposure Science and Environmental Epidemiology
  • Collection(s):
  • Main Document Checksum:
    urn:sha-512:7489ad2b38128713dfe4d908f7f5e3bc1b7a5c1fbbfd16f32ce2eaf2064cae3fceb3426e2c31c2d9645b84ff7578496d2bcd85f23a4e928174df7746f97b26c5
  • Download URL:
  • File Type:
    Filetype[PDF - 247.04 KB ]
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