Tests for Normal Mean Vectors with Monotone Incomplete Data

SYNOPTIC ABSTRACTIn this article, we consider the distributions of the Hotelling’s T2-type test statistics for mean vectors when each dataset has a monotone missing data pattern. We give the approximate upper percentiles of the simplified Hotelling’s T2-type statistics in the case of data with k-step monotone missing data patterns. We also consider multivariate multiple comparisons for mean vectors with k-step monotone missing data. Approximate simultaneous confidence intervals for pairwise comparisons among mean vectors and comparisons with a control are obtained using Bonferroni’s approximation procedure. Finally, the accuracy and asymptotic behavior of the approximations are investigated by Monte Carlo simulation.