An Evaluation of Statistical Methods for Analyzing Follow-Up Gaussian Laboratory Data with a Lower Quantification Limit

Details

• Alternative Title:
  J Biopharm Stat
• Personal Author:
  Karon, John M. ; Wiegand, Ryan E. ; van de Wijgert, Janneke H. ; Kilmarx, Peter H.
• Description:
  Laboratory data with a lower quantification limit (censored data) are sometimes analyzed by replacing non-quantifiable values with a single value equal to or less than the quantification limit, yielding possibly biased point estimates and variance estimates that are too small. Motivated by a three-period, three-treatment crossover study of a candidate vaginal microbicide in human immunodeficiency virus (HIV)-infected women, we consider four analysis methods for censored Gaussian data with a single follow-up measurement: nonparametric methods, mixed models, mixture models, and dichotomous measures of a treatment effect. We apply these methods to the crossover study data and use simulation to evaluate the statistical properties of these methods in analyzing the treatment effect in a two-treatment parallel-arm or crossover study with censored Gaussian data. Our simulated data and our mixed and mixture models consider treated follow-up data with the same variance as the baseline data or with an inflated variance. Mixed models have the correct type I error, the best power, the least biased Gaussian parameter treatment-effect estimates, and appropriate confidence interval coverage for these estimates. A crossover study analysis with a period effect can greatly increase the required study sample size. For both designs and both variance assumptions, published sample-size estimation methods do not yield a good estimate of the sample size to obtain the stated power.
• Subjects:
  Article Cross-Over Studies Data Interpretation, Statistical Female Follow-Up Studies HIV Infections Humans Laboratory Data Mixed Models Mixture Models Normal Distribution Quantification Limit

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• Source:
  J Biopharm Stat. 25(4):812-829
• Pubmed ID:
  24906060
• Pubmed Central ID:
  PMC6880227
• Document Type:
  Journal Article
• Funding:
  CC999999/ImCDC/Intramural CDC HHS/United States
• Volume:
  25
• Issue:
  4
• Collection(s):
  CDC Public Access
• Main Document Checksum:
  urn:sha256:c4e260e23a01b591e1c8712a9b8e1efc70a87e54d2e965e034be3d35e169ccc2
• Download URL:
  https://stacks.cdc.gov/view/cdc/83428/cdc_83428_DS1.pdf
• File Type:
  [PDF - 391.31 KB ]