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Adjusted Regression Trend Test for a Multicenter Clinical Trial
Author(s) -
Quan Hui,
Capizzi Thomas
Publication year - 1999
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.0006-341x.1999.00460.x
Subject(s) - statistics , estimator , mathematics , test (biology) , regression , linear regression , regression analysis , econometrics , medicine , paleontology , biology
Summary. Studies using a series of increasing doses of a compound, including a zero dose control, are often conducted to study the effect of the compound on the response of interest. For a one‐way design, Tukey et al. {1985, Biometrics 41 , 295–301) suggested assessing trend by examining the slopes of regression lines under arithmetic, ordinal, and arithmetic‐logarithmic dose scalings. They reported the smallest p‐value for the three significance tests on the three slopes for safety assessments. Capizzi et al. (1992, Biometrical Journal 34 , 275–289) suggested an adjusted trend test, which adjusts the p‐value using a trivariate t ‐distribution, the joint distribution of the three slope estimators. In this paper, we propose an adjusted regression trend test suitable for two‐way designs, particularly for multicenter clinical trials. In a step‐down fashion, the proposed trend test can be applied to a multicenter clinical trial to compare each dose with the control. This sequential procedure is a closed testing procedure for a trend alternative. Therefore, it adjusts p‐values and maintains experimentwise error rate. Simulation results show that the step‐down trend test is overall more powerful than a step‐down least significant difference test.