Testing of multivariate repeated measures data with block exchangeable covariance structure

A new hypothesis testing of equality of mean vectors in two populations using statistic for multivariate repeated measures data on q response variables at p sites or time points in a block exchangeable covariance matrix setting is proposed. The minimum sample size needed for our new test is only , unlike in Hotelling's test. The new test is very efficient in small sample scenario, when the number of observations is not adequate to estimate the dimensional unknown unstructured variance-covariance matrix. Some simulation studies are performed to compare the power of the new test and the existing test. The performance of the proposed test is demonstrated with the two medical data sets.