Allowing for informative missingness in aggregate data meta-analysis with continuous or binary outcomes: Extensions to metamiss

Anna Chaimani, Dimitris Mavridis, Julian Higgins, Georgia Salanti, Ian R White

Research output: Contribution to journalArticle (Academic Journal)

156 Downloads (Pure)

Abstract

Missing outcome data can invalidate the results of randomized trials and their meta-analysis. The impact of missing outcome data on the summary effect can be explored by assuming a relationship between the outcome in the observed and the missing participants via an informative missingness parameter (IMP). The use of IMPs in pairwise meta-analysis has been previously implemented in Stata with the metamiss command for the case of binary outcome data. This paper presents the new command metamiss2, which is an extension of metamiss for binary or continuous data in pairwise or network meta-analysis.
Original languageEnglish
Article numberst0540
Pages (from-to)716-740
Number of pages25
JournalStata Journal
Volume18
Issue number3
Publication statusPublished - 14 Sep 2018

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