%0 Journal Article
%T A Test for One-sample Repeated Measures Designs: Effect of High-dimensional Data
%A Boonyarit Choopradit
%A Samruam Chongcharoen
%J Journal of Applied Sciences
%D 2011
%I Asian Network for Scientific Information
%X High-dimensional data, the dimension p of repeated measurements per subject larger than the number n of subjects, are increasingly encountered in various areas of modern science. A test statistic for analyzing high-dimensional one-sample repeated measure designs with no specific form of variance-covariance matrix assumed is proposed. This test statistic asymptotically follows a standard normal distribution for any high dimensional data. Monte Carlo study showed that the proposed test has good power and maintain approximately the nominal level with small n and any large p. Applying the proposed test to the data from body-weight of Wistar rats example with n = 10, p = 22 is demonstrated.
%K power
%K type I error
%K hypothesis test
%K nominal level
%K Monte Carlo study
%K repeated measures
%K High-dimensional data
%U http://docsdrive.com/pdfs/ansinet/jas/2011/3285-3292.pdf