Journal
STATISTICS IN MEDICINE
Volume 27, Issue 5, Pages 711-727Publisher
WILEY
DOI: 10.1002/sim.3008
Keywords
missing data; informative priors; sensitivity analysis; meta-analysis; Bayesian methods
Categories
Funding
- MRC [MC_U105260558, MC_U105285807] Funding Source: UKRI
- Medical Research Council [MC_U105285807, MC_U105260558] Funding Source: researchfish
Ask authors/readers for more resources
Analysis of a randomized trial with missing outcome data involves untestable assumptions, such as the missing at random (MAR) assumption. Estimated treatment effects are potentially biased if these assumptions are wrong. We quantify the degree of departure from the MAR assumption by the informative missingness odds ratio (IMOR). We incorporate prior beliefs about the IMOR in a Bayesian pattern-mixture model and derive a point estimate and standard error that take account of the uncertainty about the IMOR. In meta-analysis, this model should be used for four separate sensitivity analyses which explore the impact of IMORs that either agree or contrast across trial arms on pooled results via their effects on point estimates or on standard errors. We also propose a variance inflation factor that can be used to assess the influence of trials with many missing outcomes on the meta-analysis. We illustrate the methods using a meta-analysis on psychiatric interventions in deliberate self-harm. Copyright (C) 2007 John Wiley & Sons, Ltd.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available