• We hope to release a dedicated module for this in the coming year.

• In the meantime, please consider these alternatives

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• In Stata, a simulation based approach is available in the package ipdpower by Kontopantelis

• This calculates power for complex mixed effects two-level data structures, especially focusing on a treatment-covariate interactions. However, note that it amalgamates within-trial and across-trial information, and so will give inflated estimates of power.

• For examples, type 'help ipdpower' after installing

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• In R, the ipdmeta package by Kovalchik can be used to estimate the power of an IPD meta-analysis to detect a specified treatment-covariate interaction based on entered aggregate data

• It applied to a binary or continuous outcomes and a binary or continuous covariate

• As analytic solutions are used, it is very fast; however, the binary outcome results are only an approximation. 

• For examples, see here.

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• An online calculator for an IPD meta-analysis with a continuous outcome, for estimating a treatment-covariate interaction with either a binary or continuous covariates, is given by Joie Ensor here. A video demonstration is available. This also implements the Kovalchick and Cumberland analytic approach, so has the aforementioned limitation for binary outcomes.

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