Comments on 'standard and reference-based conditional mean imputation': regulators and trial statisticians be aware!
File(s)
Author(s)
Cro, Suzie
Morris, Tim P
Roger, James H
Carpenter, James R
Type
Journal Article
Abstract
Accurate frequentist performance of a method is desirable in confirmatory clinical trials, but is not sufficient on its own to justify the use of a missing data method. Reference-based conditional mean imputation, with variance estimation justified solely by its frequentist performance, has the surprising and undesirable property that the estimated variance becomes smaller the greater the number of missing observations; as explained under jump-to-reference it effectively forces the true treatment effect to be exactly zero for patients with missing data.
Date Issued
2024-09-01
Date Acceptance
2024-04-17
Citation
Pharmaceutical Statistics: the journal of applied statistics in the pharmaceutical industry, 2024, 23 (5), pp.595-790
ISSN
1539-1604
Publisher
Wiley
Start Page
595
End Page
790
Journal / Book Title
Pharmaceutical Statistics: the journal of applied statistics in the pharmaceutical industry
Volume
23
Issue
5
Copyright Statement
Copyright © 2024 John Wiley & Sons Ltd. This is the author’s accepted manuscript made available under a CC-BY licence in accordance with Imperial’s Research Publications Open Access policy (www.imperial.ac.uk/oa-policy)
License URL
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/38631678
Subjects
clinical trial
conditional mean imputation
estimands
missing data
multiple imputation
reference‐based imputation
treatment policy
variance estimation
Publication Status
Published
Coverage Spatial
England
Date Publish Online
2024-04-17