Sensitivity analysis for a partially missing binary outcome in a two-arm randomized clinical trial.
Although recent guidelines for dealing with missing data emphasize the need for sensitivity analyses, and such analyses have a long history in statistics, universal recommendations for conducting and displaying these analyses are scarce. We propose graphical displays that help formalize and visualize the results of sensitivity analyses, building upon the idea of 'tipping-point' analysis for randomized experiments with a binary outcome and a dichotomous treatment. The resulting 'enhanced tipping-point displays' are convenient summaries of conclusions obtained from making different modeling assumptions about missingness mechanisms. The primary goal of the displays is to make formal sensitivity analysesmore comprehensible to practitioners, thereby helping them assess the robustness of the experiment's conclusions to plausible missingness mechanisms. We also present a recent example of these enhanced displays in amedical device clinical trial that helped lead to FDA approval.
Department of Statistics, Harvard University, Cambridge, MA 02138, U.S.A.
Victoria
V
Liublinska
Donald B
DB
Rubin
D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D050815:Fractures, Compression / Q000601:surgery; D006801:Humans; D058498:Kyphoplasty / Q000009:adverse effects / Q000592:standards; D015233:Models, Statistical; D010146:Pain / Q000517:prevention & control; D016032:Randomized Controlled Trials as Topic / Q000379:methods*; D016103:Spinal Fractures / Q000601:surgery; D014481:United States
graphical displays; missing data; missing data mechanism; multiple imputation; tipping-point analysis