Kalcher, K. (2009). Meta-regression and robustness [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://resolver.obvsg.at/urn:nbn:at:at-ubtuw:1-31395
meta-regression; meta-analysis; robustness; LTS; least trimmed squares; random effects; simulation
en
Abstract:
Meta-analysis is the synthesis of information from multiple primary studies of similar design. A useful meta-analytic tool is meta-regression, wich serves to assess the relation between one or more study-level covariates and the observed effect size in a study.<br />Robustness is the ability of a statistical method to cope with violation of model assumptions. Robustness is of particular importance in meta-analysis, and various reasons for this are presented. Specific issues of robustness in the context of meta-analysis are raised. A robust estimator for meta-regression, termed meta.lts, is introduced, and its usefulness is demonstrated using simulation studies.
