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Testing equality of mean vectors in a one-way MANOVA with monotone missing data
Authors:Ayaka Yagi  Muni S. Srivastava
Affiliation:1. Department of Applied Mathematics, Tokyo University of Science, Shinjuku-ku, Tokyo, Japan;2. Department of Statistical Sciences, University of Toronto, Toronto, Canada
Abstract:In this study, testing the equality of mean vectors in a one-way multivariate analysis of variance (MANOVA) is considered when each dataset has a monotone pattern of missing observations. The likelihood ratio test (LRT) statistic in a one-way MANOVA with monotone missing data is given. Furthermore, the modified test (MT) statistic based on likelihood ratio (LR) and the modified LRT (MLRT) statistic with monotone missing data are proposed using the decomposition of the LR and an asymptotic expansion for each decomposed LR. The accuracy of the approximation for the Chi-square distribution is investigated using a Monte Carlo simulation. Finally, an example is given to illustrate the methods.
Keywords:Asymptotic expansion  Chi-square distribution  Decomposition of likelihood ratio  Maximum likelihood estimator  Monte Carlo simulation.
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