Data from: Using network analysis to study behavioural phenotypes: an example using domestic dogs ...
Phenotypic integration describes the complex interrelationships between organismal traits, traditionally focusing on morphology. Recently, research has sought to represent behavioural phenotypes as composed of quasi-independent latent traits. Concurrently, psychologists have opposed latent variable...
| Main Authors: | , , , |
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| Format: | Dataset |
| Language: | English |
| Published: |
Dryad
2016
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| Subjects: | |
| Online Access: | https://dx.doi.org/10.5061/dryad.81k11 https://datadryad.org/stash/dataset/doi:10.5061/dryad.81k11 |
| Summary: | Phenotypic integration describes the complex interrelationships between organismal traits, traditionally focusing on morphology. Recently, research has sought to represent behavioural phenotypes as composed of quasi-independent latent traits. Concurrently, psychologists have opposed latent variable interpretations of human behaviour, proposing instead a network perspective envisaging interrelationships between behaviours as emerging from causal dependencies. Network analysis could also be applied to understand integrated behavioural phenotypes in animals. Here, we assimilate this cross-disciplinary progression of ideas by demonstrating the use of network analysis on survey data collected on behavioural and motivational characteristics of police patrol and detection dogs (Canis lupus familiaris). Networks of conditional independence relationships illustrated a number of functional connections between descriptors, which varied between dog types. The most central descriptors denoted desirable characteristics in ... : rawDataRaw data before any statistical analysesPatrolDog_GGM_AssociationMatrixAssociation matrix of raw correlations for patrol dogs shown in the network figureDetectionDog_GGM_AssociationMatrixAssociation matrix of raw correlations for detection dogs shown in the network figurefinalMIdata_averaged_roundedFinal set of multiply imputed data (averaged over 15 multiply imputed data sets and rounded to be integers)R script fileR script to run the analyses and reproduce the figures in the article.Rscript.RSupplementary_MaterialSupplementary Material for the article, including further details and results of the statistical analyses not included in the manuscript. ... |
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