The multivariate analysis of variance as a powerful approach for circular data.

ABSTRACT:

Background

A broad range of scientific studies involve taking measurements on a circular, rather than linear, scale (often variables related to times or orientations). For linear measures there is a well-established statistical toolkit based on linear modelling to explore the associations between this focal variable and potentially several explanatory factors and covariates. In contrast, statistical testing of circular data is much simpler, often involving either testing whether variation in the focal measurements departs from circular uniformity, or whether a single explanatory factor with two levels is supported.

Methods

We use simulations and example data sets to investigate the usefulness of a MANOVA approach for circular data in comparison to commonly used statistical t

SUBMITTER: Landler L 

PROVIDER: S-EPMC9044715 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature