MA ‐cont:pre/post effect size: An interactive tool for the meta‐analysis of continuous outcomes using R Shiny
Research Synthesis Methods, vol. 13, pp. 649–660
Abstract
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.
Authors 5
-
Leiden University Medical Center
Affiliation as printed
Clinical Epidemiology Leiden University Medical Center Leiden The Netherlands
Clinical Epidemiology Leiden University Medical Center Leiden The Netherlands
-
Affiliation as printed
Centre for Prognosis Research Research Institute for Primary Care & Health Sciences, Keele University Keele UK
Centre for Prognosis Research Research Institute for Primary Care & Health Sciences, Keele University Keele UK
-
Olaf M. Dekkers Aachen
Leiden University Medical Center
Affiliation as printed
Clinical Epidemiology Leiden University Medical Center Leiden The Netherlands
Clinical Epidemiology Leiden University Medical Center Leiden The Netherlands
-
Theo Stijnen Aachen
Leiden University Medical Center
Affiliation as printed
Biomedical Data Sciences Leiden University Medical Center Leiden The Netherlands
Biomedical Data Sciences Leiden University Medical Center Leiden The Netherlands
-
Saskia le Cessie Aachen
Leiden University Medical Center
Affiliation as printed
Biomedical Data Sciences Leiden University Medical Center Leiden The Netherlands
Clinical Epidemiology Leiden University Medical Center Leiden The Netherlands
Biomedical Data Sciences Leiden University Medical Center Leiden The Netherlands
Clinical Epidemiology Leiden University Medical Center Leiden The Netherlands
Cited by 21 stored of 21
No patents citing this paper on Lens.org (checked 2026-10-11).