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

Aleksi Kallio*

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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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.

Original languageEnglish
Article numbere0165456
Pages (from-to)1-13
JournalPloS one
Issue number11
Publication statusPublished - 1 Nov 2016
MoE publication typeA1 Journal article-refereed

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