Rank correlation inferences for clustered data with small sample size.

ABSTRACT: This paper develops methods to test for associations between two variables with clustered data using a U-Statistic approach with a second-order approximation to the variance of the parameter estimate for the test statistic. The tests that are presented are for clustered versions of: Pearsons χ ² test, the Spearman rank correlation and Kendall's τ for continuous data or ordinal data and for alternative measures of Kendall's τ that allow for ties in the data. Shih and Fay use the U-Statistic approach but only consider a first-order approximation. The first-order approximation has inflated significance level in scenarios with small sample sizes. We derive the test statistics using the second-order approximations aiming to improve the type I error

SUBMITTER: Hunsberger S 

PROVIDER: S-EPMC9355045 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature