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Non-parametric test of ordered alternatives in incomplete blocks

✍ Scribed by Eunsik Park; Young Jack Lee


Book ID
101239718
Publisher
John Wiley and Sons
Year
2000
Tongue
English
Weight
76 KB
Volume
19
Category
Article
ISSN
0277-6715

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✦ Synopsis


Often in medical studies, study subjects become a natural block of observations repeated over a time period. Some subjects miss observations, thus becoming incomplete blocks of observations. We are interested in testing an ordered alternative (or time trend), and propose a non-parametric method to detect a trend in incomplete blocks. Our approach is to estimate the trend by the linear regression method within each block and apply the one-sample Wilcoxon test to the estimated linear trends. The one-sample Wilcoxon test will be sensitive to the trend if it exists. The proposed test statistic is asymptotically normal and consistent. We can also estimate the overall magnitude of the linear trend and its conΓΏdence interval by a proper non-parametric method. By Monte Carlo studies, we compare the performance of the proposed test against extended Page and Jonckheere tests.


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In environmental and medical studies, multivariate data are often recorded over regular time intervals and examined for monotone increasing or decreasing trends in one or more of the variables. Dietz and Killeen (J. Amer. Statist. Assoc. 76 (1981) 169) proposed a non-parametric test based on the Ken