A Comparison of Two Matrices for Testing Covariance Matrix in Unbalanced Linear Mixed Models

BBarnabani M
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BBarnabani M: Department of Statistics Informatics Applications, University of Florence, Italy

Biostatistics and Biometrics Open Access Journal, 2017, vol. 3, issue 3, 66-67

Abstract: Despite the widespread use of mixed-effects regression model, available methods for testing the covariance matrix of random effects are quite limited. In these cases, because of complexity and difficulties coming from an analysis of multiple variance components, inference based on testing the equality of two positive semi definite matrices seems most appropriate.

Keywords: Biometrics Open Access Journal; Biostatistics and Biometrics; Biostatistics and Biometrics Open Access Journal; Open Access Journals; biometrics journal; biometrics articles; biometrics journal reference; biometrics journal impact factor; biometrics and biostatistics journal impact factor; journal of biometrics; open access juniper publishers; juniper publishers reivew (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:adp:jbboaj:v:3:y:2017:i:3:p:66-67

DOI: 10.19080/BBOAJ.2017.03.555612

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