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STATISTICAL APPROACHES TO ANALYZE CENSORED DATA WITH MULTIPLE DETECTION LIMITS

ZHONG, WEI
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1130204124

Abstract Details

2005, PhD, University of Cincinnati, Medicine : Biostatistics (Environmental Health).
Censored data with multiple detection limits frequently arise in environmental health studies, where data are collected by different sampling and measured by different analytical procedures or when data are combined from multiple laboratories. The substitution method is the most common approach to handle censored environmental data; however, this method lacks a theoretical basis and results can differ substantially depending on the substituted value. Maximum likelihood estimation (MLE) with the Expectation-Maximization (EM) algorithm integrated method and the meta-analysis method were studied to determine if they can overcome these problems and to incorporate the sample collection process into the estimation of summary statistics. A new likelihood-based Z-score test and a resampling-based permutation test were introduced as well to compare the means of two censored data groups. They were expected to provide higher power and closer type I error rates to the nominal level than the usual two-sample t-test. The proposed methods were evaluated through a series of simulation studies and their performances were compared to those of the conventional methods. Simulation results consistently showed that the proposed MLE with the EM algorithm integrated method and the meta-analysis method provided the most accurate and efficient estimation of summary statistics for censored data with multiple detection limits. The simulation also suggested that the amount of censoring, magnitude of variance and disparities of sample size influenced the statistical estimation. The proposed Z-score test and permutation test were superior to the usual two-sample t-test. They provided better power and type I error rates in the simulation studies, and thus should be recommended for the comparison of means between two censored data groups. The proposed methods were successfully applied to two data sets collected by environmental health studies; the obtained summary statistics and significant test results were found to be similar to the published findings.
Dr. Rakesh Shukla (Advisor)
163 p.
censored data; multiple detection limits; lognormal distribution; EM algorithm; meta-analysis; permutation test

Recommended Citations

Citations

  • ZHONG, W. (2005). STATISTICAL APPROACHES TO ANALYZE CENSORED DATA WITH MULTIPLE DETECTION LIMITS [Doctoral dissertation, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1130204124

    APA Style (7th edition)

  • ZHONG, WEI. STATISTICAL APPROACHES TO ANALYZE CENSORED DATA WITH MULTIPLE DETECTION LIMITS. 2005. University of Cincinnati, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1130204124.

    MLA Style (8th edition)

  • ZHONG, WEI. "STATISTICAL APPROACHES TO ANALYZE CENSORED DATA WITH MULTIPLE DETECTION LIMITS." Doctoral dissertation, University of Cincinnati, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1130204124

    Chicago Manual of Style (17th edition)

ucin1130204124
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© 2005, all rights reserved.
This open access ETD is published by University of Cincinnati and OhioLINK.