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

Suzie Cro, Gordon Forbes, Nicholas A. Johnson, Brennan C. Kahan
2020 BMC Medicine  
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. A review of randomised trials published between January and April 2018 in six
more » ... ading 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. 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. Unexplained discrepancies in the statistical methods of randomised trials are common. Increased transparency is required for proper evaluation of results.
doi:10.1186/s12916-020-01590-1 pmid:32466758 fatcat:mrqbxaz4h5e3fdc3vqpvyd6bce