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Re: st: meta-analysis graphs with metan

From   Roger Newson <[email protected]>
To   [email protected]
Subject   Re: st: meta-analysis graphs with metan
Date   Tue, 22 Mar 2005 20:33:33 +0000

At 18:23 22/03/2005, Michael McCulloch wrote:
Metan is a very useful routine for calculating summary effect measures. However, I am having a problem with balancing text size of study ID (namevar) with the width of the text columns where event counts are displayed. Here's the problem:
1. If I set texts to display at full size texts=1, then the text for the event counts in group 1 overlaps with that of group 2.
2. If I set texts to display at reduced size (texts=0.7), then the event counts text columns are properly separated, but the study ID text (namevar) is so small it is unsuitable for publication.

I should add that the # of events is large, four digits, making the display issue more problematic. Techniques for customizing the graph are only minimally documented in "help metan."

I'd greatly appreciate any suggestions on how to customize the graph. Especially helpful would be suggestions on how to increase the width between the event counts text columns.
I don't have much experience with -metan-. However, if you want the full power of Stata 8 graphics (including the -ysize()- option), then you might like to use the -eclplot- package, downloadable from SSC, to create forest plots. -eclplot- inputs a dataset (or resultsset) with 1 observation per confidence interval to be displayed, and data on estimates, confidence limits and (optionally) study sizes, and produces as output a confidence interval plot (optionally horizontal like a Cochrane forest plot), with the option of weighting the estimate symbols (or even the confidence limit caps) by study size. The plot can be customized using the -plot()- option and other Stata 8 graphics options.

To create the input dataset in the first place, a useful tool might be the -metaparm- package, also downloadable from SSC. -metaparm- takes, as input, a dataset with 1 observation per study and data on estimates, standard errors and (optionally) by-groups, and creates, as output, an output dataset (or resultsset) with one observation, or one observation per by-group, and data on estimates, confidence limits and numbers of subjects for the overall summary parameter. This resultsset can be -append-ed to the original dataset to produce a dataset ready to input to -eclplot- to produce the forest plot.

I hope this helps.


Roger Newson
Lecturer in Medical Statistics
Department of Public Health Sciences
Division of Asthma, Allergy and Lung Biology
King's College London

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United Kingdom

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Email: [email protected]

Opinions expressed are those of the author, not the institution.

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