Nonparametric Tests of Trend for Proportions

Abstract

A general method is proposed for constructing nonparametric tests of trend for proportions. Such alternatives arise in situations where it is of interest to test for monotonicity in rates of growth. The class of tests is based on the ranks of the observations. The general approach consists of defining two sets of rankings: the first describes the time and the other the binary data itself. The test tatistic measures the similarity between the two sets. The asymptotic null distributions are determined for similarity measures due to Spearman, Kendall and Hamming. A limited simulation study shows that the Spearman test has greater power.