Potentially missing data are considerably more frequent than definitely missing data: a methodological survey of 638 randomized controlled trials

Missing data for the outcomes of participants in randomized controlled trials (RCTs) are a key element of risk of bias assessment. However, it is not always clear from RCT reports whether some categories of participants were followed-up or not (i.e., do or do not have missing data) nor how the RCT authors dealt with missing data in their analyses. Our objectives were to describe how RCT authors (1) report on different categories of participants that might have missing data, (2) handle these categories in the analysis, and (3) judge the risk of bias associated with missing data.

Source: Journal of Clinical Epidemiology - October 6, 2018 Category: Epidemiology Authors: Lara A. Kahale, Batoul Diab, Assem M. Khamis, Yaping Chang, Luciane Cruz Lopes, Arnav Agarwal, Ling Li, Reem A. Mustafa, Serge Koujanian, Reem Waziry, Jason W. Busse, Abeer Dakik, Gordon Guyatt, Elie A. Akl Tags: Review Source Type: research