Properties of fixed-fixed models and alternatives in presence-absence data analysis

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Volume Title
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Date
2016-11-01
Department
Department of Computer Science
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Mcode
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Language
en
Pages
1-13
Series
PLOS ONE, Volume 11, issue 11
Abstract
Assessing the significance of patterns in presence-absence data is an important question in ecological data analysis, e.g., when studying nestedness. Significance testing can be performed with the commonly used fixed-fixed models, which preserve the row and column sums while permuting the data. The manuscript considers the properties of fixed-fixed models and points out how their strict constraints can lead to limited randomizability. The manuscript considers the question of relaxing row and column sun constraints of the fixed-fixed models. The Rasch models are presented as an alternative with relaxed constraints and sound statistical properties. Models are compared on presence-absence data and surprisingly the fixed-fixed models are observed to produce unreasonably optimistic measures of statistical significance, giving interesting insight into practical effects of limited randomizability.
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Kallio , A 2016 , ' Properties of fixed-fixed models and alternatives in presence-absence data analysis ' , PloS one , vol. 11 , no. 11 , e0165456 , pp. 1-13 . https://doi.org/10.1371/journal.pone.0165456