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Social LearningAn Introduction to Mechanisms, Methods, and Models$
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William Hoppitt and Kevin N. Laland

Print publication date: 2013

Print ISBN-13: 9780691150703

Published to Princeton Scholarship Online: October 2017

DOI: 10.23943/princeton/9780691150703.001.0001

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Statistical Methods for Diffusion Data

Statistical Methods for Diffusion Data

Chapter:
(p.105) Chapter 5 Statistical Methods for Diffusion Data
Source:
Social Learning
Author(s):

William Hoppitt

Kevin N. Laland

Publisher:
Princeton University Press
DOI:10.23943/princeton/9780691150703.003.0005

This chapter describes statistical methods for inferring and quantifying social transmission in groups of animals in the wild, or in “captive” groups of animals in naturalistic social environments. In particular, it considers techniques for analyzing time-structured data on the occurrence of a particular behavior pattern, or behavioral trait, in one or more groups. For the most part, the focus is on cases where a novel trait spreads through one or more groups. Following standard terminology in the field of social learning, the spread of a trait through a group is referred to as a diffusion, and the resulting data as diffusion data. The methods include diffusion curve analysis and network-based diffusion analysis. For the latter, inclusion of individual-level variables is taken into account, along with model selection and inference, modeling of multiple diffusions, choosing a social network, and “untransmitted” social effects. The chapter also examines the spatial spread of a behavioral trait.

Keywords:   statistical methods, social transmission, animals, behavioral trait, social learning, diffusion, diffusion data, diffusion curve analysis, network-based diffusion analysis, social network

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