|Title||User-written packages for meta-analysis in Stata|
Jonathan A. C. Sterne, University of Bristol
Ross J. Harris, University of Bristol
Roger M. Harbord, University of Bristol
Thomas J. Steichen, RJRT
|Date||January 2007; updated June 2013|
Stata does not have a meta-analysis command. Stata users, however, have developed an excellent suite of commands for performing meta-analyses.
In 2009, Stata published Meta-Analysis in Stata: An Updated Collection from the Stata Journal, which brought together all the Stata Journal articles about meta-analysis. This book is available for purchase at stata-press.com/books/meta-analysis-in-stata/.
We have created a command to download all user-written commands discussed in the body of the book. For instructions on obtaining this command, see stata-press.com/data/mais.html.
The following meta-analysis commands are all described in Meta-Analysis in Stata: An Updated Collection from the Stata Journal.
metan is the main Stata meta-analysis command. Its latest version allows the user to input the cell frequencies from the 2 × 2 table for each study (for binary outcomes), the mean and standard deviation in each group (for numerical outcomes), or the effect estimate and standard error from each study. It provides a comprehensive range of methods for meta-analysis, including inverse-variance–weighted meta-analysis, and creates new variables containing the treatment effect estimate and its standard error for each study. These variables can then be used as input to other Stata meta-analysis commands. Meta-analyses may be conducted in subgroups by using the by() option.
All the meta-analysis calculations available in metan are based on standard methods, an overview of which may be found in chapter 15 of Deeks, Altman, and Bradburn (2001).
The version of the metan command that used Stata 7 graphics has been renamed metan7 and is downloaded as part of the metan package currently available on the SSC archive.
The most recent help file for metan provides several clickable examples of using the command.
labbe draws a L’Abbe plot for event data (proportions of successes in the two groups).
metacum performs cumulative meta-analyses and graphs the results.
metap combines p-values by using Fisher’s method, Edgington’s additive method, or Edgington’s normal curve method. It was released in 1999 as a version 6 command (no graphics) and was last updated in 2000. It requires the user to input a p-value for each study.
metareg does meta-regression. It was first released in 1998 and has been updated to take account of improvements in Stata estimation facilities and recent methodological developments. It requires the user to input the treatment effect estimate and its standard error for each study.
metafunnel plots funnel plots. It was released in 2004 and uses Stata 8 graphics. It requires the user to input the treatment effect estimate and its standard error for each study.
confunnel plots contour-enhanced funnel plots. The command has been designed to be flexible, allowing the user to add extra features to the funnel plot.
metabias provides statistical tests for funnel plot asymmetry. It was first released in 1997, but it has been updated to provide recently proposed tests that maintain better control of the false-positive rate than those available in the original command.
metatrim implements the “trim and fill” method to adjust for publication bias in funnel plots. It requires the user to input the treatment effect estimate and its standard error for each study.
metandi facilitates the fitting of hierarchical logistic regression models for meta-analysis of diagnostic test accuracy studies. metandiplot produces a graph of the model fit by metandi, which must be the last estimation-class command executed.
glst calculates a log-linear dose–response regression model using generalized least squares for trend estimation of single or multiple summarized dose–response epidemiological studies. Output from this command may be useful in deriving summary effects and their standard errors for inclusion in meta-analyses of such studies.
metamiss performs meta-analysis with binary outcomes when some or all studies have missing data.
mvmeta performs maximum likelihood, restricted maximum likelihood, or method-of-moments estimation of random-effects multivariate meta-analysis models. mvmeta_make facilitates the preparation of summary datasets from more detailed data.
The following commands are documented in the Appendix:
metannt is intended to aid interpretation of meta-analyses of binary data by presenting intervention effect sizes in absolute terms, as the number needed to treat (NNT) and the number of events avoided (or added) per 1,000. The user inputs design parameters, and metannt uses the metan command to calculate the required statistics. This command is available as part of the metan package.
metaninf is a port of the metainf command to use metan as its analysis engine rather than meta. It was released in 2001 as a version 6 command using version 6 graphics and was last updated in 2004. It requires the user to provide input in the form needed by metan. To install the package, type ssc install metaninf in Stata.
midas provides statistical and graphical routines for undertaking meta-analysis of diagnostic test performance in Stata. To install the package, type ssc install midas in Stata.
meta_lr graphs positive and negative likelihood ratios in diagnostic tests. It can do stratified meta-analysis of individual estimates. The user must provide the effect estimates (log positive likelihood ratio and log negative likelihood ratio) and their standard errors. Commands meta and metareg are used for internal calculations. This is a version 8 command released in 2004. To install the package, type ssc install meta_lr in Stata.
metaparm performs meta-analyses and calculates confidence intervals and p-values for differences or ratios between parameters for different subpopulations for data stored in the parmest format. To install the package, type ssc install metaparm in Stata.
The following command appeared in the Stata Journal after the
publication of Meta-Analysis in Stata: An Updated Collection from the
metaan performs meta-analysis on effect estimates and standard errors. Included are profile likelihood and permutation estimation, two algorithms not available in metan.
The following commands appeared in the Stata Journal after the publication of
Meta-Analysis in Stata: An Updated Collection from the Stata Journal.
metacumbounds provides z-values, p-values, and Lan-DeMets bounds obtained from fixed- or random-effects meta-analysis. It plots the boundries and z-values through a process.
extfunnel implements a new range of overlay augmentations to the funnel plot to assess the impact of a new study on an existing meta-analysis.