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

Ian White and Julian Higgins
Additional contact information
Julian Higgins: University of Bristol

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. metamiss and metamiss2 are different commands with overlapping functions. Users with binary outcomes including reasons for missing data should use metamiss. Other users should use metamiss2.

Language: Stata
Requires: Stata version 10.1
Keywords: meta-analysis; missing data; binary outcome; informative missingness (search for similar items in EconPapers)
Date: 2007-09-07, Revised 2022-05-28
Note: This module should be installed from within Stata by typing "ssc install metamiss". 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.
References: Add references at CitEc
Citations:

Downloads: (external link)
http://fmwww.bc.edu/repec/bocode/m/metamiss.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/m/metamiss.sthlp 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)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:boc:bocode:s456869

Ordering information: This software item can be ordered from
http://repec.org/docs/ssc.php

Access Statistics for this software item

More software in Statistical Software Components from Boston College Department of Economics Boston College, 140 Commonwealth Avenue, Chestnut Hill MA 02467 USA. Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F Baum ().