Thus based on the values P/V or (1-P)/V the Miller back transform is either used (but N replaced by 1/V) or the simple back transform, P, is retained. However, we must use the simple back-conversion, (SIN(t/2))^2, when P/V or (1-P)/V) is less than 2 to avoid the back-transform from bombing out.
The difference is because after extensive simulations we realized that for meta-analysis we should use 1/V in place of use of harmonic N for back conversion as that was not meant for meta-analysis.
Input str23 study int n byte(a b c) int d float qi byte(q1 q2 q3 q4 q5) float(r1 r2 r3 r4 r5) I will now try to catch up!Ĭode: * Example generated by -dataex.
MRC Clinical Trials Unit at UCL, London, UKĮ-mail: Apologies to anyone who has started threads here, or replied to existing threads, with issues related to admetan, ipdmetan or forestplot (or, indeed, metan) over the last couple of months I've been putting all my energy into getting this update out. I hope you find the updated package useful. If all else fails, the previous version of metan is still available within the package under the name metan9.ado. Since this is such a major update, there are bound to be teething troubles so please don't hesitate to contact me ( with any bugs or other issues. However, ipdmetan remains as a separate package - albeit with a dependency on metan - and will continue to be maintained (a small update to ipdmetan is also now available via SSC). The older programs call metan from within them, and *should* still work OK (due to our desire for the update to be seamless), but it is recommended that metan now be used instead, with the options cumulative, influence or proportion as required (see documentation).Īs a result of this update, the admetan package will no longer be maintained.
metan now incorporates the functionality of the user-written programs metacum, metaninf and metaprop, respectively for cumulative and influence meta-analysis and meta-pooling of proportions. This can also be combined with a (single) subgroup variable with by(). All pooled results, heterogeneity statistics etc. Presented weights are taken from the first model in the list. A major new feature: the results of multiple models - inverse-variance, Mantel-Haenszel, DerSimonian-Laird, REML, and so on - may be presented simultaneously beneath the list of individual studies on-screen and in a forest plot. (However, note that previously-returned statistics such as r(RR) are still, additionally, available.) This avoids confusion when comparing between models (see below) and enables standardised interface with other commands. Returned and saved effect sizes, standard errors and confidence intervals are *always* on the interval/log scale, even with Mantel-Haenszel methods. If the user also wishes to see I-squared as derived from tau-squared and sigma-squared (see Higgins & Thompson 2002), they may use the option isqparam (see documentation). Tau-squared is reported in a separate table. using the Mantel-Haenszel log-effect size and weights) rather than on tau-squared. Standard heterogeneity output, including I-squared, is always based on a single Q statistic calculated directly from the data (either Cochran's Q, or a common-effect alternative e.g. However, all new behaviour, and differences from the previous version and from Stata 16's meta suite, are fully documented in the *.sthlp files. Much of the "new" functionality is simply carried over from admetan, and as such is described in this thread. We have also ensured that all default behaviour is in keeping with current best practice in the field. An important aspect of this work has been to make the update as seamless as possible - that is, to enable existing metan users to continue to use the command in the same way as before, if they so wish. Over the past year I have worked with Professor Jonathan Sterne, a co-author of metan, and Professor Julian Higgins - both eminent figures in the meta-analysis field - to make this happen. One of the discussions that emerged was the possibility of merging admetan with the ever-popular but venerable metan, which had not been updated for a decade and currently has no dedicated support. With thanks as ever to Kit Baum, I am excited to announce a major update to the user-written command "metan", version 4.0, now available via SSC.įirstly, a bit of history: as described in this thread I previously released v3.x of the admetan / ipdmetan meta-analysis command suite, and presented it at the 2018 London UK Stata Conference.
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