Analysis of social interactions in group-housed animals using dyadic linear models

TL;DR

This paper introduces a Bayesian statistical model for analyzing dyadic social interactions among group-housed animals, validated through multiple cross-validation strategies on pig behavior data, highlighting the significance of prior nursery experience.

Contribution

It presents a novel Bayesian generalized linear mixed model specifically designed for dyadic animal interaction data, with comprehensive validation strategies and application to real pig behavior data.

Findings

Prior nursery mate experience significantly affects aggression.

Weak correlation between aggression giver and receiver effects.

Model performance varies with validation strategy, lower for group-based validation.

Abstract

Understanding factors affecting social interactions among animals is important for applied animal behavior research. Thus, there is a need to elicit statistical models to analyze data collected from pairwise behavioral interactions. In this study, we propose treating social interaction data as dyadic observations and propose a statistical model for their analysis. We performed posterior predictive checks of the model through different validation strategies: stratified 5-fold random cross-validation, block-by-social-group cross-validation, and block-by-focal-animals validation. The proposed model was applied to a pig behavior dataset collected from 797 growing pigs freshly remixed into 59 social groups that resulted in 10,032 records of directional dyadic interactions. The response variable was the duration in seconds that each animal spent delivering attacks on another group mate. Generalized linear mixed models were fitted. Fixed effects included sex, individual weight, prior nursery mate experience, and prior littermate experience of the two pigs in the dyad. Random effects included aggression giver, aggression receiver, dyad, and social group. A Bayesian framework was utilized for parameter estimation and posterior predictive model checking. Prior nursery mate experience was the only significant fixed effect. In addition, a weak but significant correlation between the random giver effect and the random receiver effect was obtained when analyzing the attacking duration. The predictive performance of the model varied depending on the validation strategy, with substantially lower performance from the block-by-social-group strategy than other validation strategies. Collectively, this paper demonstrates a statistical model to analyze interactive animal behaviors, particularly dyadic interactions.