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st: metan v9 update
Dear Stata users
Thanks to Kit Baum, an updated version of the meta-analysis package -metan-
is now available from the SSC archive.
In addition to providing a comprehensive range of options for meta-analysis
of 2x2 tables and of mean differences, these routines provide methods for
the meta-analysis of summary (aggregate) data (for example the log odds
ratio and its standard error) from each study. Tests of the null hypothesis
that the summary treatment effect is null are reported, as well as a test
for heterogeneity (whether the true effect in all studies is the same).
Heterogeneity is also quantified using the I-squared statistic (Higgins et
al 2003).
The original code for -metan- was written by Mike Bradburn, Jon Deeks and
Doug Altman. Those of you familiar with the original -metan- command as
updated over the years will find everything works much as it used to. As
before, the results may be displayed graphically in a forest plot, and the
-by- option may be used to produce and display results in subgroups.
However, the graph routines have now been completely re-written and several
new features added:
� Version 9 graphics: it is possible to use Stata 9 graphics options to
change all aspects of the forest plot
� Flexible, tabular display with the option to display addition columns of
data on either side of the forest plot
� Summary results from meta-analyses using two different methods may be
displayed together in the forest plot. Alternatively, summary estimates may
be suppressed.
� The predictive distribution of random effects analyses may be displayed
as an extended confidence interval as described by Higgins and Thompson
(2006)
All of these features (and more) are explained in the help file, which
contains several clickable examples showing the use of the new command.
To install -metan-, please type:
-ssc install metan-
and to view the help file
-help metan-
Comments and suggestions are welcome, and should be sent to
[email protected].
We are grateful to Patrick Royston (MRC Clinical Trials Unit, London UK)
and to Vince Wiggins and Jeff Pitblado (StataCorp) for extensive advice and
suggestions. We hope that the new features are useful.
Best wishes,
Ross Harris, Roger Harbord and Jonathan Sterne
Department of Social Medicine, University of Bristol UK
www.epi.bris.ac.uk
References
Higgins JPT, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in
meta-analyses. BMJ 2003; 327:557-560.
http://dxi.org/10.1136/bmj.327.7414.557
Higgins JPT, Thompson SG (2006) Presenting random effects meta-analyses:
where we are going wrong? (from presentation, work in preparation)
----------------------
Ross Harris
Department of Social Medicine
University of Bristol
+44 (0)117 928 7338
[email protected]
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