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.
en
dc.language
English
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dc.language.iso
en
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dc.rights.uri
http://rightsstatements.org/vocab/InC/1.0/
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dc.subject
Meta-Regression
de
dc.subject
Meta-Analyse
de
dc.subject
Robustheit
de
dc.subject
LTS
de
dc.subject
Zufällige Effekte
de
dc.subject
Simulation
de
dc.subject
meta-regression
en
dc.subject
meta-analysis
en
dc.subject
robustness
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dc.subject
LTS
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dc.subject
least trimmed squares
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dc.subject
random effects
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dc.subject
simulation
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dc.title
Meta-regression and robustness
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dc.type
Thesis
en
dc.type
Hochschulschrift
de
dc.rights.license
In Copyright
en
dc.rights.license
Urheberrechtsschutz
de
dc.contributor.affiliation
TU Wien, Österreich
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dc.rights.holder
Klaudius Kalcher
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tuw.version
vor
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tuw.thesisinformation
Technische Universität Wien
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tuw.publication.orgunit
E105 - Institut für Statistik und Wahrscheinlichkeitstherorie
