Bayesian Reanalysis of Statistically Nonsignificant Outcomes in Plastic Surgery Clinical Trials

Background:. Statistically nonsignificant randomized clinical trial (RCT) results are challenging to interpret, as they are unable to prove the absence of a difference between treatment groups. Bayesian analysis offers an alternative statistical framework capable of providing a comprehensive understanding of nonsignificant results. Methods:. This cross-sectional study conducted a post hoc Bayesian analysis of statistically nonsignificant outcomes from RCTs published in Plastic and Reconstructive Surgery from 2013 to 2022. Bayes factors representing the probability of the absence of a difference, or the null hypothesis of no difference, were calculated and examined. P values and Bayes factors of these outcomes were also compared with assessment of their association. Results:. In 73 studies with 176 statistically nonsignificant outcomes, 160 (91%) indicated evidence for the absence of a difference (Bayes factor > 1). For 110 (63%) of these, the Bayes factor was between 1 and 3, indicating weak evidence for the absence of a difference; 16 (9.1%) results supported the presence of a difference (Bayes factor < 1). A greater P value was independently associated with a larger Bayes factor (β = 2.6, P