Valid methods for meta-analyses with few studies or small sample sizes - Part II

• Applicants: Professor Dr. Tim Friede; Professor Dr. Markus Pauly
• Subject Area: Epidemiology and Medical Biometry/Statistics
• Term: since 2018
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 413270747

The main goal is to develop valid methods for meta-analyses that lead to trustworthy results even under difficult conditions. The challenges are (i) heterogeneity between studies, (ii) unbalanced designs, (iii) small or moderate numbers of cases, and (iv) few studies or (v) aggregated results from previous meta-analyses. While conventional methods often reach their limits at this point, methods are needed that reliably deliver valid results so that, for example, confidence intervals reliably reach their nominal coverage probability. For this purpose, modern Bayesian, bootstrap, resampling and statistical learning techniques, as well as robust sandwich estimators will be used, investigated or combined. After the main focus in the first project phase was on "classical" treatment effect estimators (such as standardized mean differences), the second project phase will in particular focus on restricted interval estimators (such as proportions or correlations). These estimators make it even more difficult to justify the common normal distribution assumption especially in cases (iii) and (iv). For this purpose, we will develop new methods for univariate and multivariate fixed- and random-effects models as well as mixed-effects meta-regression models. Furthermore, regression approaches will be investigated to map more complex component interventions or to account for possible selection mechanisms (publication bias). To give recommendations for their adequate use, the developed methods will be extensively investigated in simulation studies and exemplary applied to current data sets. In addition, analysis approaches based on meta-analysis databases will be empirically evaluated. The methods are also implemented in freely available open-source software, which will be documented in an easy understandable way. This will not only increase the transparency of published simulation results, but also provides easy access to the methods developed in the project for a wider audience of applied users . As in the first phase, the continuation of the project will be supported by renowned Mercator Fellows.

• DFG Programme: Research Grants