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help for ^galbr^                                 (STB-41: sbe20; STB-56: sbe20.1)
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Assessing heterogeneity in meta-analysis: the Galbraith plot
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^galbr^ theta setheta [^if^ exp] [^in^ range] [, ^id(^strvar^)^ graph_options]


Description
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^galbr^ provides a graphical display to get a visual impression of the amount of
heterogeneity from a meta-analysis. For each trial, the z statistic 
^theta/setheta^ is plotted against the reciprocal standard error ^1/setheta^. 
The (unweighted) regression line constrained through the origin, with its 95% 
confidence interval, has a slope equal to the overall log rate ratio, 
or log odds ratio, or log hazard ratio in a fixed effects meta-analysis. 
The position of each trial on the horizontal axis gives an indication of the 
weight allocated to it in a meta-analysis. The position on the vertical axis
gives the contribution of each trial to the Q statistic for heterogeneity.
In the absence of heterogeneity we could expect all the points to lie within 
the confidence bounds (positioned 2 units over and below the regression line).

^theta^ is the effect estimated from the individual study, and ^setheta^ is
its standard error. For example theta might be a difference in means, a
log rate ratio, a log odds ratio or a log hazard ratio.

If you have a dataset which contains data for all studies, then the @byvar@
command can be used to derive the effect estimates and standard errors for the
individual studies. For example:

. ^sort study^
. ^byvar study, coef(group) se(group) generate:^
. ^quietly poisson cases group, e(pyrs)^
. ^sort study^
. ^qui by study: keep if _n==1^
. ^rename _C_1 logrr^
. ^rename _S_1 se^
. ^galbr logrr se, id(study) yline(0)^

Alternatively, the @collapse@ command may be useful.


Options
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Graph options are allowed, but ^ylabel()^, ^yscale()^, ^xscale()^, ^symbol()^
are not suggested.

^id(^labelvar^)^ supplied any variable, which is used to label the studies. 
If the data contains a labeled numeric variable, it can also be used.

^yline(^0^)^ is a useful to check it with the direction and intensity of the 
overall effect estimated in a fixed effects meta-analysis by the slope
of the (unweighted) regression line constrained through the origin.    


Author
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       Aurelio Tobias
       Universidad Miguel Hernandez, Alicante, Spain
       email: bledatobias@@ctv.es


Also see
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    STB: STB-41 sbe20, STB-38 sbe16 
On-line: help for @graph@, @byvar@, @collapse@, @for@, @meta@ (if installed), 
         @metareg@ (if installed), @metabias@ (if installed), @metacum@ (if
         installed), @metainf@ (if installed) 
