Non-parametric test of ordered alternatives in incomplete blocks.
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 confidence 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. Published in 2000 by John Wiley & Sons, Ltd.
Park
E
E
Biometry and Mathematical Statistics Branch, National Institutes of Health, 6100 Executive Blvd, Room 7B13, Rockville, MD 20892, USA.
Lee
Y J
YJ
D000328:Adult; D001786:Blood Glucose / Q000032:analysis; D003198:Computer Simulation; D003920:Diabetes Mellitus / Q000378:metabolism; D005260:Female; D006801:Humans; D009010:Monte Carlo Method; D011247:Pregnancy; D011261:Pregnancy Trimester, First; D011254:Pregnancy in Diabetics / Q000378:metabolism*; D012044:Regression Analysis; D018709:Statistics, Nonparametric
D001786:Blood Glucose