those to be used in particular statistical analyses. It is important to check that no errors are introduced when merging the datasets. Therefore, it is sensible to calculate summary statistics (e.g. number of participants in each group, mean age, proportion of women, overall treatment effect) for each trial before (in the pre‐merge dataset) and after (in the merged dataset), to ensure they agree exactly. A single dataset comprising IPD from all trials will not be achievable if the IPD for some can only be accessed remotely, but the central research team can still proceed with a two-stage meta‐analysis as described in Chapter 5.
Figure 4.13 Example of items to include in summary of finalised trial IPD for verification by a trial investigator.
Source: Ruth Walker and Lesley Stewart.
4.10 Concluding Remarks
There is no doubt that development of the project protocol, managing a large‐scale collaboration and carefully collecting, processing and checking data is a lengthy and resource‐intensive phase of an IPD meta‐analysis project. However, these aspects are key to ensuring that the approach is scientifically rigorous and truly collaborative, and that the privacy of the participants in the included trials is maintained. Importantly, it also ensures that the collated IPD is as accurate, up to date, reliable and comprehensive as it can be, and that it is well understood by the central research team. In all, this provides a necessary solid foundation for the statistical analysis part of the IPD project that follows.
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