Evidence of unexplained discrepancies between planned and conducted statistical analyses: a review of randomised trials

BMC Med. 2020 May 29;18(1):137. doi: 10.1186/s12916-020-01590-1.

Abstract

Background: Choosing or altering the planned statistical analysis approach after examination of trial data (often referred to as 'p-hacking') can bias the results of randomised trials. However, the extent of this issue in practice is currently unclear. We conducted a review of published randomised trials to evaluate how often a pre-specified analysis approach is publicly available, and how often the planned analysis is changed.

Methods: A review of randomised trials published between January and April 2018 in six leading general medical journals. For each trial, we established whether a pre-specified analysis approach was publicly available in a protocol or statistical analysis plan and compared this to the trial publication.

Results: Overall, 89 of 101 eligible trials (88%) had a publicly available pre-specified analysis approach. Only 22/89 trials (25%) had no unexplained discrepancies between the pre-specified and conducted analysis. Fifty-four trials (61%) had one or more unexplained discrepancies, and in 13 trials (15%), it was impossible to ascertain whether any unexplained discrepancies occurred due to incomplete reporting of the statistical methods. Unexplained discrepancies were most common for the analysis model (n = 31, 35%) and analysis population (n = 28, 31%), followed by the use of covariates (n = 23, 26%) and the approach for handling missing data (n = 16, 18%). Many protocols or statistical analysis plans were dated after the trial had begun, so earlier discrepancies may have been missed.

Conclusions: Unexplained discrepancies in the statistical methods of randomised trials are common. Increased transparency is required for proper evaluation of results.

Keywords: P-hacking; Randomised controlled trials; Statistical analysis; Statistical analysis plan; Transparency.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Data Interpretation, Statistical*
  • Humans
  • Randomized Controlled Trials as Topic