Title: Meta-regression and robustness
Language: English
Authors: Kalcher, Klaudius 
Qualification level: Diploma
Keywords: Meta-Regression; Meta-Analyse; Robustheit; LTS; Zufällige Effekte; Simulation
meta-regression; meta-analysis; robustness; LTS; least trimmed squares; random effects; simulation
Advisor: Filzmoser, Peter
Issue Date: 2009
Number of Pages: 87
Qualification level: Diploma
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.
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.
URI: https://resolver.obvsg.at/urn:nbn:at:at-ubtuw:1-31395
http://hdl.handle.net/20.500.12708/12537
Library ID: AC07805943
Organisation: E105 - Institut für Statistik und Wahrscheinlichkeitstherorie 
Publication Type: Thesis
Hochschulschrift
Appears in Collections:Thesis

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