Estimation of multivariate treatment effects in contaminated clinical trials

Research output: Contribution to journalArticlepeer-review

Abstract

The paper addresses estimating and testing treatment effects with multivariate outcomes in clinical trials where imperfect diagnostic devices are used to assign subjects to treatment groups. The paper focuses on the pre-post design and proposes two novel methods for estimating and testing treatment effects. In addition, methods for sample size and power calculations are developed. The methods are compared with each other and with a traditional method in a simulation study. The new methods show significant advantages in terms of power, coverage probability, and required sample size. The application of the methods is illustrated with data from electroencephalogram (EEG) recordings of alcoholic and control subjects.

Original languageEnglish
Pages (from-to)535-565
Number of pages31
JournalPharmaceutical Statistics
Volume21
Issue number3
DOIs
StatePublished - May 1 2022

Bibliographical note

Funding Information:
The authors are thankful to the associate editor and the anonymous reviewers for the valuable comments that helped to improve the manuscript substantially. The authors are also thankful to the editor for the orderly handling of this submission. The research of Zi Ye was partially done while she was pursuing her PhD at the University of Kentucky. She would like to express her gratitude to the Dr. Bing Zhang Department of Statistics.

Publisher Copyright:
© 2021 John Wiley & Sons Ltd.

Keywords

  • EM algorithm
  • F-approximation
  • finite mixture
  • method of moments
  • sample size determination

ASJC Scopus subject areas

  • Statistics and Probability
  • Pharmacology
  • Pharmacology (medical)

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