PLoS ONE (Jan 2020)

Diagnosing fraudulent baseline data in clinical trials

  • Michael A. Proschan,
  • Pamela A. Shaw,
  • Vance Berger

Journal volume & issue
Vol. 15, no. 9

Abstract

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The first table in many articles reporting results of a randomized clinical trial compares baseline factors across arms. Results that appear inconsistent with chance trigger suspicion, and in one case, accusation and confirmation of data falsification. We confirm theoretically results of simulation analyses showing that inconsistency with chance is extremely difficult to prove in the absence of any information about correlations between baseline covariates. We offer a reasonable diagnostic to trigger further investigation.