ObjectivesTo assess biostatistical quality of study protocols submitted to German medical ethics committees according to personal appraisal of their statistical members.DesignWe conducted a web-based survey among biostatisticians who have been active as members in German medical ethics committees during the past 3 years.SettingThe study population was identified by a comprehensive web search on websites of German medical ethics committees.ParticipantsThe final list comprised 86 eligible persons. In total, 57 (66%) completed the survey.QuestionnaireThe first item checked whether the inclusion criterion was met. The last item assessed satisfaction with the survey. Four items aimed to characterise the medical ethics committee in terms of type and location, one item asked for the urgency of biostatistical training addressed to the medical investigators. The main 2×12 items reported an individual assessment of the quality of biostatistical aspects in the submitted study protocols, while distinguishing studies according to the German Medicines Act (AMG)/German Act on Medical Devices (MPG) and studies non-regulated by these laws.Primary and secondary outcome measuresThe individual assessment of the quality of biostatistical aspects corresponds to the primary objective. Thus, participants were asked to complete the sentence ‘In x% of the submitted study protocols, the following problem occurs’, where 12 different statistical problems were formulated. All other items assess secondary endpoints.ResultsFor all biostatistical aspects, 45 of 49 (91.8%) participants judged the quality of AMG/MPG study protocols much better than that of ‘non-regulated’ studies. The latter are in median affected 20%–60% more often by statistical problems. The highest need for training was reported for sample size calculation, missing values and multiple comparison procedures.ConclusionsBiostatisticians being active in German medical ethics committees classify the biostatistical quality of study protocols as low for ‘non-regulated’ studies, whereas quality is much better for AMG/MPG studies.
Revisiting the Two Predominant Statistical Problems: The Stopping-rule Problem and the Catch-all Hypothesis Problem
