Modeling Social Dominance: Elo-Ratings, Prior History, and the Intensity of Aggression.

Among studies of social species, it is common practice to rank individuals using dyadic social dominance relationships. The Elo-rating method for achieving this is powerful and increasingly popular, particularly among studies of nonhuman primates, but suffers from two deficiencies that hamper its usefulness: an initial burn-in period during which the model is unreliable and an assumption that all win-loss interactions are equivalent in their influence on rank trajectories. Here, I present R code that addresses these deficiencies by incorporating two modifications to a previously published function, testing this with data from a 9-mo observational study of social interactions among wild male chimpanzees (Pan troglodytes) in Uganda. I found that, unmodified, the R function failed to resolve a hierarchy, with the burn-in period spanning much of the study. Using the modified function, I incorporated both prior knowledge of dominance ranks and varying intensities of aggression. This effectively eliminated the burn-in period, generating rank trajectories that were consistent with the direction of pant-grunt vocalizations (an unambiguous demonstration of subordinacy) and field observations, as well as showing a clear relationship between rank and mating success. This function is likely to be particularly useful in studies that are short relative to the frequency of aggressive interactions, for longer-term data sets disrupted by periods of lower quality or missing data, and for projects investigating the relative importance of differing behaviors in driving changes in social dominance. This study highlights the need for caution when using Elo-ratings to model social dominance in nonhuman primates and other species.