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Statistical Issues on Analysis of Censored Data Due to Detection Limit

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Listed:
  • Hua He
  • Xuenan Mi
  • Jerry Cornell
  • Wan Tang
  • Tanika Kelly
  • Hui Shen
  • Hongwen Deng
  • Yan Du

Abstract

Measures of substance concentration in urine, serum or other biological matrices often have an assay limit of detection. When concentration levels fall below the limit, the exact measures cannot be obtained, and thus are left censored. Common practice for addressing the censoring issue is to delete or 'fill-in' the censored observations in data analysis, which often results in biased or non-efficient estimates. Assuming the concentration or transformed concentration follows a normal distribution, a Tobit regression model can be applied. When the study population is heterogeneous, for example due to the existence of a latent group of subjects who lack the substance, the problem becomes more challenging. In this paper, we conduct intensive simulation studies to investigate the statistical issues in analyzing censored data and compare different methods in which the data are treated either as a dependent variable or an independent variable. We also analyze triclosan data in the NHANES study and metabolites data in the Bogalusa Heart Study to illustrate the issues. Some guidelines for analyzing such censored data are provided.

Suggested Citation

  • Hua He & Xuenan Mi & Jerry Cornell & Wan Tang & Tanika Kelly & Hui Shen & Hongwen Deng & Yan Du, 2020. "Statistical Issues on Analysis of Censored Data Due to Detection Limit," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 9(4), pages 1-49, July.
    • Handle: RePEc:ibn:ijspjl:v:9:y:2020:i:4:p:49
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    References listed on IDEAS

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    2. McDonald, John F & Moffitt, Robert A, 1980. "The Uses of Tobit Analysis," The Review of Economics and Statistics, MIT Press, vol. 62(2), pages 318-321, May.
    3. Rosen, Harvey S, 1976. "Taxes in a Labor Supply Model with Joint Wage-Hours Determination," Econometrica, Econometric Society, vol. 44(3), pages 485-507, May.
    4. Michael C. Keeley & Philip K. Robins & Robert G. Spiegelman & Richard W. West, 1978. "The Labor-Supply Effects and Costs of Alternative Negative Income Tax Programs," Journal of Human Resources, University of Wisconsin Press, vol. 13(1), pages 3-36.
    5. Amemiya, Takeshi, 1984. "Tobit models: A survey," Journal of Econometrics, Elsevier, vol. 24(1-2), pages 3-61.
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    Cited by:

    1. Eunsil Seok & Akhgar Ghassabian & Yuyan Wang & Mengling Liu, 2024. "Statistical Methods for Modeling Exposure Variables Subject to Limit of Detection," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 16(2), pages 435-458, July.

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