Skip to main content

Table 4 Handling of missing data in the principal analysis of the 140 studies that reported some missing data in their primary outcome and performed an analysis

From: Current practice in analysing and reporting binary outcome data—a review of randomised controlled trial reports

Approach to handling missing data in the principal analysis

 Available cases

96 (69%)

 Multiple imputation

9 (6%)

 Worst-case/best-case scenario

18 (13%)

 Last observation carried forward

2 (1%)

 Other1

1 (1%)

 Unclear

14 (10%)

Performance of appropriate2 sensitivity analysis for missing data

17 (12%)

  1. 1In one study, missing outcomes were imputed by independent assessors using a pre-defined set of rules provided in a supplementary appendix
  2. 2Defined as an analysis that varies the assumptions made about the underlying missing data mechanism