Meta-analysis is a widely used methodology to combine evidence from different sources examining a common research phenomenon, to obtain a quantitative summary of the studied phenomenon. In the medical field, multiple studies investigate the effectiveness of new treatments and meta-analysis is largely performed to generate the summary (average) treatment effect. In the meta-analysis of aggregate continuous outcomes measured in a pretest-posttest design using differences in means as the effect measure, a plethora of methods exist: analysis of final (follow-up) scores, analysis of change scores and analysis of covariance. Specialised and general-purpose statistical software is used to apply the various methods, yet, often the choice among them depends on data availability and statistical affinity. We present a new web-based tool, MA-cont:pre/post effect size, to conduct meta-analysis of continuous data assessed pre- and post-treatment using the aforementioned approaches on aggregate data and a more flexible approach of generating and analysing pseudo individual participant data. The interactive web environment, available by R Shiny, is used to create this free-to-use statistical tool, requiring no programming skills by the users. A basic statistical understanding of the methods running in the background is a prerequisite and we encourage the users to seek advice from technical experts when necessary.
Keywords: ANCOVA; baseline imbalance; pseudo individual participant data; shiny.
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