ArticleMovement ecology2022
The multivariate analysis of variance as a powerful approach for circular data.
Article in Movement ecology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Directionality range in Emlen funnels.Journal of the Royal Society, Interface · 2026Pooled it
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- Synchronized by photoperiod: Shedding light on flowering seasonality in Acrocomia species (Arecaceae).PloS one · 2026Article
- The Effect of High-Voltage Power Lines on Magnetic Orientation of Domestic Dogs.Animals : an open access journal from MDPI · 2025Article
- A bone tool used by neanderthal for flaying carcasses at the Abri du Maras (France).Scientific reports · 2025Article
- Daily activity patterns in agoutis (Heliyon · 2024Article
- Development of a multisensor biologging collar and analytical techniques to describe high-resolution spatial behavior in free-ranging terrestrial mammals.Ecology and evolution · 2024Article
- Revisiting Perdeck's massive avian migration experiments debunks alternative social interpretations.Biology letters · 2024Article
- A GPS assisted translocation experiment to study the homing behavior of red deer.Scientific reports · 2024Article
- Life tables in entomology: A discussion on tables' parameters and the importance of raw data.PloS one · 2024Article
- Evaluating the power of a recent method for comparing two circular distributions: an alternative to the Watson UScientific reports · 2023Article
- Distinctive Effects of D1 and D2 Receptor Agonists on Cortico-Basal Ganglia Oscillations in a Rodent Model of L-DOPA-Induced Dyskinesia.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2023Article
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Authors and funding
3 authors.
Funding
Abstract
backgroundA 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.
methodsWe use simulations and example data sets to investigate the usefulness of a MANOVA approach for circular data in comparison to commonly used statistical tests.
resultsHere we demonstrate that a MANOVA approach based on the sines and cosines of the circular data is as powerful as the most-commonly used tests when testing deviation from a uniform distribution, while additionally offering extension to multi-factorial modelling that these conventional circular statistical tests do not.
conclusionsThe herein presented MANOVA approach offers a substantial broadening of the scientific questions that can be addressed statistically using circular data.
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