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Multivariate Longitudinal Analysis with Bivariate Correlation Test

By Eric Houngla Adjakossa, Ibrahim Sadissou, Mahouton Norbert Hounkonnou and Gregory Nuel

Abstract

International audienceIn the context of multivariate multilevel data analysis, this paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the dimensional residual terms are assumed uncorrelated. Using the EM algorithm, we suggest more general expressions of the model's parameters estimators. These estimators can be used in the framework of the multivariate longitudinal data analysis as well as in the more general context of the analysis of multivariate multilevel data. By using a likelihood ratio test, we test the significance of the correlations between the random effects of two dependent variables of the model, in order to investigate whether or not it is useful to model these dependent variables jointly. Simulation studies are done to assess both the parameter recovery performance of the EM estimators and the power of the test. Using two empirical data sets which are of longitudinal multivariate type and multivariate multilevel type, respectively, the usefulness of the test is illustrated

Topics: Multivariate data analysis, parameter estimator, [ MATH.MATH-ST ] Mathematics [math]/Statistics [math.ST], [ SDV.IMM ] Life Sciences [q-bio]/Immunology, [ SDV.MHEP.MI ] Life Sciences [q-bio]/Human health and pathology/Infectious diseases, [ SHS.EDU ] Humanities and Social Sciences/Education
Publisher: Public Library of Science
Year: 2016
DOI identifier: 10.1371/journal.pone.0159649
OAI identifier: oai:HAL:hal-01378473v1
Provided by: Hal-Diderot

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