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All Times EDT

Wednesday, September 23
Wed, Sep 23, 1:30 PM - 2:45 PM
Virtual
Adjusting for Prognostic Baseline Variables to Improve Precision and Power in Randomized Trials

Re-Randomization Tests with Adaptive Regression (301262)

*Michael Proschan, National Institute of Allergy and Infectious Diseases, NIH 

Keywords: randomized trial analysis

It is well known that adjustment for covariates can improve power in randomized clinical trials, but in a new disease, the best prognostic covariates may not be known. In adaptive regression, covariates are not pre-specified, but are selected based on their ability to predict the outcome in the current trial. One promising method of analyzing results from such a trial is a re-randomization test that fixes data at their observed values and re-randomizes according to the trial’s randomization scheme to generate a reference distribution for the test statistic. This talk compares different valid methods of adaptive regression analyzed using a re-randomization test. Are there extreme settings under which these methods break down? What is the proper conclusion following a statistically significant result? These are some of the questions answered in this talk.