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Multilevel modeling analysis of dyadic network data with an application to Ye'kwana food sharing
Author(s) -
Koster Jeremy,
Leckie George,
Miller Andrew,
Hames Raymond
Publication year - 2015
Publication title -
american journal of physical anthropology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.146
H-Index - 119
eISSN - 1096-8644
pISSN - 0002-9483
DOI - 10.1002/ajpa.22721
Subject(s) - multilevel model , computer science , interpersonal communication , social network analysis , focus (optics) , data science , econometrics , psychology , social psychology , mathematics , machine learning , social media , world wide web , physics , optics
Behavioral ecologists have recently begun using multilevel modeling for the analysis of social behavior. We present a multilevel modeling formulation of the Social Relations Model that is well suited for the analysis of dyadic network data. This model, which we adapt for count data and small datasets, can be fitted using standard multilevel modeling software packages. We illustrate this model with an analysis of meal sharing among Ye'kwana horticulturalists in Venezuela. In this setting, meal sharing among households is predicted by an association index, which reflects the amount of time that members of the households are interacting. This result replicates recent findings that interhousehold food sharing is especially prevalent among households that interact and cooperate in multiple ways. We discuss opportunities for human behavioral ecologists to expand their focus to the multiple currencies and cooperative behaviors that characterize interpersonal relationships in preindustrial societies. We discuss possible extensions to this statistical modeling approach and applications to research by human behavioral ecologists and primatologists. Am J Phys Anthropol 157:507–512, 2015. © 2015 Wiley Periodicals, Inc.