Tests for no treatment effect in randomized clinical trials

M. H. Gail, W. Y. Tan, S. Piantadosi

Research output: Contribution to journalArticlepeer-review

100 Scopus citations

Abstract

We propose a test of the null hypothesis of no treatment effect in a randomized clinical trial that is based on the randomization distribution of residuals. These residuals result from regressing the response on covariates, but not treatment. In contrast to model-based score tests, this procedure maintains nominal size when the model is misspecified, and, in particular, when relevant covariates are omitted from the regression. The efficiency of the procedure is evaluated for regressions with some, but not all, required covariates. For many generalized linear models and survival models, conventional model-based score tests are shown to have supranominal size when relevant covariates are omitted, but logistic regression and the proportional hazards model are robust.

Original languageEnglish (US)
Pages (from-to)57-64
Number of pages8
JournalBiometrika
Volume75
Issue number1
DOIs
StatePublished - Mar 1988
Externally publishedYes

Keywords

  • Analysis of covariance
  • Nonlinear regression
  • Randomization
  • Randomized clinical trial
  • Robust test

ASJC Scopus subject areas

  • Statistics and Probability
  • General Mathematics
  • Agricultural and Biological Sciences (miscellaneous)
  • General Agricultural and Biological Sciences
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

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