Meta-analysis is a standard statistical method used to combine the conclusions of individual studies that are related and the results of single study alone can not answered to deal with issues. The data are summarized by one or more outcome measure estimates along with their standard errors. The multivariate model and the variations between studies are not considered in most articles. Here we discuss multivariate effects models: a multivariate fixed effects model and a multivariate random effects model.
@article{bwmeta1.element.bwnjournal-article-doi-10_7151_dmps_1062,
author = {Iwona Janicka},
title = {Combining multivariate estimators of the mean vector},
journal = {Discussiones Mathematicae Probability and Statistics},
volume = {25},
year = {2005},
pages = {77-89},
zbl = {1102.62058},
language = {en},
url = {http://dml.mathdoc.fr/item/bwmeta1.element.bwnjournal-article-doi-10_7151_dmps_1062}
}
Iwona Janicka. Combining multivariate estimators of the mean vector. Discussiones Mathematicae Probability and Statistics, Tome 25 (2005) pp. 77-89. http://gdmltest.u-ga.fr/item/bwmeta1.element.bwnjournal-article-doi-10_7151_dmps_1062/
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