Assessment of assumptions of statistical analysis methods in randomised clinical trials: the what and how

When analysing and presenting results of randomised clinical trials, trialists rarely report if or how underlying statistical assumptions were validated. To avoid data-driven biased trial results, it should be common practice to prospectively describe the assessments of underlying assumptions. In existing literature, there is no consensus on how trialists should assess and report underlying assumptions for the analyses of randomised clinical trials. With this study, we developed suggestions on how to test and validate underlying assumptions behind logistic regression, linear regression, and Cox regression when analysing results of randomised clinical trials. Two investigators compiled an initial draftbased on a review of the literature. Experienced statisticians and trialists from eight different research centres and trial units then participated in a anonymised consensus process, where we reached agreement on the suggestions presented in this paper. This paper provides detailed suggestions on 1) which underlying statistical assumptions behind logistic regression, multiple linear regression and Cox regression each should be assessed; 2) how these underlying assumptions may be assessed; and 3) what to do if these assumptions are violated. We believe that the validity of randomised clinical trial results will increase if our recommendations for assessing and dealing with violations of the underlying statistical assumptions are followed.

Automated summary

Trialists often fail to report if or how underlying statistical assumptions were validated when analysing and presenting results of randomised clinical trials, which may lead to biased trial results. A lack of consensus on how to assess and report underlying assumptions in the existing literature prompted the development of suggestions to guide trialists in testing and validating these assumptions. Collaborative efforts between statisticians and trialists from different research centres resulted in detailed recommendations on assessing and addressing violations of underlying statistical assumptions to improve the validity of randomised clinical trial results.