CEMIMIX: Stata module to perform reference-based multiple imputation of cost-effectiveness data in clinical trials

Baptiste Leurent () and Suzie Cro ()
Additional contact information
Baptiste Leurent: UCL Department of Statistical Science
Suzie Cro: Imperial College London, UK

Statistical Software Components from Boston College Department of Economics

Abstract: The cemimix module imputes missing numerical cost and/or effectiveness variables following a reference-based multiple imputation approach. It follows the method described in Leurent et al. (Pharmacoeconomics 2020), based on the work by Carpenter, Roger, and Kenward (Journal of Biopharmaceutical Statistics, 2013). It allows for various missing data assumptions, including 'Missing at random' (MAR), 'Jump to reference' (J2R), 'Copy increments in reference' (CIR), 'Last mean carried forward (LMCF), and 'Baseline mean carried forward' (BMCF). It was primarily developed for the imputation of cost-effectiveness data in randomised controlled trials but can be used more generally for the imputation of up to two continuous outcomes, measured at a single follow-up point or longitudinally (repeated measures).

Language: Stata
Requires: Stata version 15
Keywords: multiple imputation; cost effectiveness; clinical trials (search for similar items in EconPapers)
Date: 2022-07-08
Note: This module should be installed from within Stata by typing "ssc install cemimix". The module is made available under terms of the GPL v3 (https://www.gnu.org/licenses/gpl-3.0.txt). Windows users should not attempt to download these files with a web browser.
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Downloads: (external link)
http://fmwww.bc.edu/repec/bocode/c/cemimix.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/c/cemimix.sthlp help file (text/plain)
http://fmwww.bc.edu/repec/bocode/_/10TT.dta sample data file (application/x-stata)

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