A Test of Non Null Hypothesis for Linear Trends in Proportions

作者：Zhao, Guolong^*

来源：Communications in Statistics - Theory and Methods, 2015, 44(8): 1621-1639.

DOI：10.1080/03610926.2013.776687

• Least squares
• Linear trend
• Non null hypothesis
• Proportion
• Statistical test

Usual tests for trends stand under null hypothesis. This article presents a test of non null hypothesis for linear trends in proportions. A weighted least squares method is used to estimate the regression coefficient of proportions. A non null hypothesis is defined as its expectation equal to a prescribed regression coefficient margin. Its variance is used to construct an equation of basic relationship for linear trends in proportions along the asymptotic normal method. Then follow derivations for the sample size formula, the power function, and the test statistic. The expected power is obtained from the power function and the observed power is exhibited by Monte Carlo method. It reduces to the classical test for linear trends in proportions on setting the margin equal to zero. The agreement between the expected and the observed power is excellent. It is the non null hypothesis test matched with the classical test and can be applied to assess the clinical significance of trends among several proportions. By contrast, the classical test is restricted in testing the statistical significance. A set of data from a website is used to illustrate the methodology.

• 出版日期2015
• 单位河南省医药科学研究院; 郑州大学