Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Annamaria Guolo, Cristiano Varin
Title: The R Package metaLik for Likelihood Inference in Meta-Analysis
Abstract: Meta-analysis is a statistical method for combining information from different studies about the same issue of interest. Meta-analysis is widely diffuse in medical investigation and more recently it received a growing interest also in social disciplines. Typical applications involve a small number of studies, thus making ordinary inferential methods based on first-order asymptotics unreliable. More accurate results can be obtained by exploiting the theory of higher-order asymptotics. This paper describes the metaLik package which provides an R implementation of higher-order likelihood methods in meta-analysis. The extension to meta-regression is included. Two real data examples are used to illustrate the capabilities of the package.

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Paper: The R Package metaLik for Likelihood Inference in Meta-Analysis     Download PDF (Downloads: 1950)
metaLik_0.31.tar.gz: R source package Download (Downloads: 469; 13KB)
v50i07.R: R example code from the paper Download (Downloads: 578; 721B)
erratum_2014_02_08.txt: Erratum Download (Downloads: 332; 303B)

DOI: 10.18637/jss.v050.i07

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.