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New Regression Models with Egocentric Social Network Data

An Analysis of Political Party Preference in Japan

Bibliographic Data

ID11010606
AuthorsKazuo Yamaguchi (0000-0002-5439-7432)
Year2013
Volume43
Issue1
Pages312-345
Publication date2013-08-01
Open AccessYes
TypeARTICLE
VenueSociological Methodology (JOURNAL)
Journal identifiersISSN: 0081-1750 • E-ISSN: 1467-9531
PublisherSAGE Publications (PUBLISHER • US)
DOI10.1177/0081175013490189
OpenAlexW2018884824
LanguageEN
Citations received1
References cited27

This paper introduces some regression models for a categorical dependent variable with data from egocentric social networks as covariates to analyze the determinants of the outcome for the subject and the determinants of the extent of agreement in the outcome between the subject and the people socially connected to the subject. The merits of the models introduced in this paper are their wide applicability to surveys that collect data on egocentric social networks and their ability to identify the determinants of agreement between subjects’ and their friends’ attitudinal or behavioral outcomes, controlling for the tendency to agree because of homophily in the choice of friends. An illustrative application from the Japanese General Social Survey data shows that several substantively distinct characteristics of egocentric networks affect subjects’ political party preferences and the extent of agreement between the political party preferences of subjects and their significant others

Affect (linguistics · Categorical variable · Covariate · Econometrics · Economics · General Social Survey · Homophily · Machine learning · Microeconomics · Outcome (game theory · Regression · Regression analysis · Social media · Social network (sociolinguistics · Statistics · Subject (documents · Survey data collection · Variables · Complex Network Analysis Techniques · Computer Science · Mathematics · Opinion Dynamics and Social Influence · Psychology · Social and Cultural Dynamics · Social Psychology

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Citations per year0.09
Citation span2015 - 2015 (1)
Highly citedNo

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