METAMISS: Stata module to perform meta-analysis with missing data

Ian White () and Julian Higgins
Additional contact information
Ian White: MRC Biostatistics Unit
Julian Higgins: MRC Biostatistics Unit

Statistical Software Components from Boston College Department of Economics

Abstract: metamiss performs meta-analysis with a binary outcome, using data on the number of successes, number of failures and number of missing values by arm. A variety of imputation methods are available, including imputing failures, imputing successes, worst- and best-case. Different imputation schemes may be applied to subgroups with different reported reasons for missing data. The degree of informative missingness may be specified via the informative missingness odds ratio (IMOR) in each group. Finally, uncertainty about the IMORs may be taken into account in a Bayesian analysis. This command should be especially useful for sensitivity analysis.

Language: Stata
Requires: Stata version 9
Keywords: meta-analysis; missing data; binary outcome; informative missingness (search for similar items in EconPapers)
Date: Written 2007-09-07
Note: This module may be installed from within Stata by typing "ssc install metamiss". Windows users should not attempt to download these files with a web browser.

Downloads: (external link)
http://fmwww.bc.edu/repec/bocode/m/metamiss.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/m/metamiss.hlp help file (text/plain)
http://fmwww.bc.edu/repec/bocode/h/haloperidol.do examples file (text/plain)
http://fmwww.bc.edu/repec/bocode/h/haloperidol.dta sample data file (application/x-stata)

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