Circular statistics meets practical limitations: a simulation-based Rao's spacing test for non-continuous data.

ABSTRACT:

Background

For data collected on a circular rather than linear scale, a very common procedure is to test whether the underlying distribution appears to deviate from circular uniformity. Rao's spacing test is often used to evaluate the support the data offers for the null hypothesis of uniformity. Here we demonstrate that the traditional version of this test fails to adequately control type I error rate when the data is non-continuous (i.e. is rounded/grouped to a finite number of discrete values, e.g. to the nearest degree, a common situation). To overcome this issue, we provide a numerically-intensive simulation version of the test.

Methods

We use a simulation study to explore the performance of the traditional and our novel variant on Rao's spacing test, both in terms of c

SUBMITTER: Landler L 

PROVIDER: S-EPMC6511169 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature