A Reproducibility Rule for Choosing the Number of Imputations When Reporting Clinical Trials. (2nd October 2021)

• Record Type: Journal Article
• Authors: Gorst-Rasmussen, Anders
• Is Part Of: Statistics in biopharmaceutical research. Volume 13:Number 4(2021)
• Page Start: 455
• Page End: 460
• Publication Date: 2021-10-02
• Subjects: Missing data -- Multiple imputation -- Replication; Pharmacy -- Statistical methods -- Periodicals; Pharmaceutical biotechnology -- Statistical methods -- Periodicals; Biopharmaceutics -- Periodicals; Biometry -- Periodicals; Pharmacy -- Statistical methods; Periodicals; 615.190727
• DOI: 10.1080/19466315.2020.1784781
• Languages: English
• ISSNs: 1946-6315

Abstract

Abstract: The use of multiple imputation (MI) to address missing data has improved the quality of clinical trial reporting but has also introduced the nuisance of results that are subject to sampling variability introduced by using a finite number of imputations. There is a tradeoff between ensuring that enough imputations are used to obtain accurate results for decision making while at the same time keeping the number of imputations low enough to avoid computational bottlenecks. We propose a rule for evaluating this tradeoff that extends the familiar idea of exact reproducibility of statistical results: enough imputations are used if an independent round of MI yields exactly the same result when rounded to the chosen reporting precision, with high probability. We explore how this reproducibility rule can be used derive simple criteria for choosing the number of imputations at the planning stage of a clinical trial.