Combining multivariate estimators of the mean vector

• Autorzy: Iwona Janicka
• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

meta-analysis; the fixed effects model; the random effects model

Kategorie tematyczne

• 92D30: Epidemiology
• 62P10: Applications to biology and medical sciences
• 62N02: Estimation
• 62H12: Estimation
• 62H10: Distribution of statistics
• 92C60: Medical epidemiology

• Wydawca: Faculty of Mathematics, Computer Science and Econometrics, University of Zielona Góra
• Czasopismo: Discussiones Mathematicae Probability and Statistics
• Rocznik: 2005
• Tom: 25
• Numer: 1
• Strony: 77-89

Daty

wydano

2005

otrzymano

2004-04-10

Twórcy

autor

Iwona Janicka

• Adam Mickiewicz University, Umultowska 87, 61-614 Poznań, Poland

Bibliografia

• [1] S.E. Brockwell and I.R. Gordon, A comparison of statistical methods for meta - analysis, Statistics In Medicine 20 (2001), 825-840.
• [2] R. DerSimonian and N. Laird, Meta-analysis in clinical trials, Controlled Clinical Trials 7 (1986), 177-188.
• [3] L.V. Hedges and I. Olkin, Statistical Methods for meta- Analysis, Academic Press, Orlando 1985.
• [4] S.L. Normand, Tutorial in biostatistics. Meta-analysis: formulating, evaluating, combining, and reporting, Statistics In Medicine 18 (1999), 321-359.

Identyfikatory

DOI

10.7151/dmps.1062