Properties of Fixed-Fixed Models and Alternatives in Presence-Absence Data Analysis

• Published in: PloS one Vol. 11; no. 11; p. e0165456
• Main Author: Kallio, Aleksi
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 03.11.2016; Public Library of Science (PLoS)
• Subjects: Biogeography; Biology and Life Sciences; Comparative analysis; Constraint modelling; Data analysis; Data Interpretation, Statistical; Data mining; Data processing; Ecological and Environmental Phenomena; Ecological monitoring; Ecology; Ecology and Environmental Sciences; Evolution; Information management; Knowledge discovery; Markov analysis; Mathematical models; Models, Statistical; Physical Sciences; Properties (attributes); Research and Analysis Methods; Statistical analysis; Stochastic Processes; Finland
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0165456

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.