2014
DOI: 10.1007/s40273-014-0193-3
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A Guide to Handling Missing Data in Cost-Effectiveness Analysis Conducted Within Randomised Controlled Trials

Abstract: Missing data are a frequent problem in cost-effectiveness analysis (CEA) within a randomised controlled trial. Inappropriate methods to handle missing data can lead to misleading results and ultimately can affect the decision of whether an intervention is good value for money. This article provides practical guidance on how to handle missing data in within-trial CEAs following a principled approach: (i) the analysis should be based on a plausible assumption for the missing data mechanism, i.e. whether the prob… Show more

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Cited by 490 publications
(623 citation statements)
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“…Missing data on costs and clinical effects for the various follow‐up periods were imputed using multiple imputation by chained equations (MICE) as implemented in STATA 14 (Van Buuren, Boshuizen, & Knook, 1999). For this, we made the assumption that data were “missing at random” (Faria, Gomes, Epstein, & White, 2014). Imputations were performed separately for the intervention and the control group within each study.…”
Section: Methodsmentioning
confidence: 99%
“…Missing data on costs and clinical effects for the various follow‐up periods were imputed using multiple imputation by chained equations (MICE) as implemented in STATA 14 (Van Buuren, Boshuizen, & Knook, 1999). For this, we made the assumption that data were “missing at random” (Faria, Gomes, Epstein, & White, 2014). Imputations were performed separately for the intervention and the control group within each study.…”
Section: Methodsmentioning
confidence: 99%
“…MI of both costs and QALYs is increasingly recognised as an appropriate approach to deal with missing observation and missing follow-up data (29). All missing cost and utility data were treated as missing at random.…”
Section: Missing Datamentioning
confidence: 99%
“…The imputations were conducted in STATA version 13, using predictive mean matching and sequential chained equations. The variables included in the models were selected on the basis of potential predictive ability identified from descriptive and regression analyses of the pooled baseline and follow up data (29).…”
Section: Missing Datamentioning
confidence: 99%
“…54 Current guidance on handling missing data in cost-effectiveness analysis was followed to inform such analysis. 55 Only missing utility scores (for both EQ-5D-3L index and SF-6D utilities) and individual cost items were imputed and the distribution of responses for both instruments was reported for data available.…”
Section: Discussionmentioning
confidence: 99%