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Table 2 Description of the simulated scenarios when K=3 biomarker subsets (k=A,B,C)

From: Enrichment Bayesian design for randomized clinical trials using categorical biomarkers and a binary outcome

Scenarios Subset A Subset B Subset C Theoretical Values
Outcomes p1A p0A p1B p0B p1C p0C θA θB θC RR
Scenario 1 0.40 0.40 0.40 0.40 0.40 0.40 1.000 1.000 1.000 1.000
Scenario 2 0.32 0.40 0.32 0.40 0.32 0.40 0.800 0.800 0.800 0.800
Scenario 3 0.40 0.40 0.40 0.40 0.20 0.50 1.000 1.000 0.400 0.769
Scenario 4 0.40 0.40 0.24 0.40 0.24 0.40 1.000 0.600 0.600 0.733
Scenario 5 0.40 0.40 0.24 0.40 0.20 0.50 1.000 0.600 0.400 0.646
Scenario 6 0.40 0.40 0.24 0.40 0.50 0.40 1.000 0.600 1.250 0.925
Scenario 7 0.40 0.40 0.20 0.50 0.50 0.40 1.000 0.400 1.250 0.846
  1. Here, pjk denotes the probability of death in the arm j in the subset k, and θk denotes the relative risk of death in the experimental versus the control arm in subset k. RR refers to the overall treatment effect.
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BMC Medical Research Methodology

ISSN: 1471-2288

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