.- help for ^galbr^ (STB-41: sbe20; STB-56: sbe20.1) .- Assessing heterogeneity in meta-analysis: the Galbraith plot ------------------------------------------------------------ ^galbr^ theta setheta [^if^ exp] [^in^ range] [, ^id(^strvar^)^ graph_options] Description ----------- ^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 ------- 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 ------- Aurelio Tobias Universidad Miguel Hernandez, Alicante, Spain email: bledatobias@@ctv.es Also see -------- 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)