Why are There not More Bayesian Clinical Trials? Ability to Interpret Bayesian and Conventional Statistics Among Medical Researchers

Abstract

Objective and background: We assessed current understandings in interpretation of Bayesian and traditional statistical results within the clinical researcher (non-statistician) community.

Methods: Within a 22-question survey, including demographics and experience and comfort levels with Bayesian analyses, we included questions on how to interpret both Bayesian and traditional statistical outputs. We also assessed whether Bayesian or traditional interpretations are considered more useful.

Results: Among the 323 respondent clinicians, 42.4% and 36.5% chose the correct interpretations of the posterior probability and 95% credible interval, respectively. Only 11.5% of respondents interpreted the p-value correctly and 23.5% interpreted the 95% confidence interval correctly.

Conclusions: Based on these survey results, we conclude that most of these clinicians face uncertainty when attempting to interpret results from both Bayesian and traditional statistical outputs. When presented with accurate interpretations, clinicians generally conclude that Bayesian results are more useful than conventional ones. We believe there is a need for education of clinicians in statistical interpretation in ways that are customized to this audience.

Keywords: Bayesian education; Bayesian methods; Bayesian perceptions; Clinical trials; Medical school training.