Suggested CitationДЄll material on this site has been provided by the respective publishers and authors. I will take you on a quick tour of admetan and forestplot and hope to encourage you (and your colleagues and collaborators!) to use them in preference to metan.

Not only is the forest plot engine much more efficient and capable of better plots вЂout of the boxвЂ™ when compared with metan it also allows the user to save and edit вЂforestplot results setsвЂ™ which are interpreted directly by the stand-alone program forestplot to produce fully flexible plots. Another important aspect of ipdmetan (and hence also admetan) is its forest plot capabilities. The co-author and maintainer of metan, Ross Harris, has confirmed to me that he is no longer in a position to maintain it and is happy for admetan to take its place. The second stage, performed using the AD command admetan, has now been expanded into a fully comprehensive AD MA command, with all the functionality of metan and much more besides. The two stages are fitting a given model to the data from each study in turn and combining the results using AD techniques. I have previously described (Fisher 2015) a user-written command, ipdmetan, which facilitates so-called вЂtwo-stageвЂ™ IPD MA. The alternative to AD MA is to obtain and analyse individual participant data (IPD), where the totality of data from all studies are stacked to form a single, large dataset. 2008) is by far the most popular Stata command for performing AD MA, but it was last updated in 2010 and has various flaws and limitations. The user-written command metan (Harris et al. Traditionally, MA is performed on aggregated data (AD), where each observation represents the effect observed in a study, often derived from study publications.

Meta-analysis (MA) is a statistical technique for combining results from multiple independent studies, with the aim of estimating a single overall effect with a size, direction and precision consistent with the data.

Meta comprehensive meta analysis