A multiplicative random effects model for meta-analysis with application to estimation of admixture component.
A multiplicative random effects model is constructed for combining results from different studies. An EM algorithm is developed for the maximum likelihood estimator under the Empirical Bayes framework. The method is applied to estimation of the admixture component in admixed populations. The admixture estimates can be useful in genetic epidemiology and DNA fingerprinting.
Li
Z
Z
Division of Biostatistics, Washington University School of Medicine, St. Louis, Missouri 63110, USA.
D001741:Black or African American; D000465:Algorithms; D000483:Alleles; D001699:Biometry; D044383:Black People / Q000235:genetics; D016172:DNA Fingerprinting; D004812:Epidemiologic Methods; D005787:Gene Frequency; D005826:Genetics, Medical; D006801:Humans; D008433:Mathematics; D015201:Meta-Analysis as Topic; D015233:Models, Statistical; D011336:Probability; D011897:Random Allocation; D014481:United States