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A Liang-Zeger Method for Modeling Dyadic Interdependence in the Analysis of Social Networks

Datos Bibliográficos

ID6169909
AutoresKazuo Yamaguchi (0000-0002-5439-7432, University of Chicago)
Año2003
Volumen33
Número1
Páginas343-380
Fecha de publicación2003-08-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaSociological Methodology (JOURNAL)
Identificadores de la revistaISSN: 0081-1750 • E-ISSN: 1467-9531
EditorialSAGE Publishing (PUBLISHER • US)
DOI10.1111/j.0081-1750.2003.00135.x
OpenAlexW1998708037
IdiomaEN
Citas recibidas2
Referencias citadas20

This article introduces a modified Liang-Zeger method for the estimation of the variance-covariance matrix of parameter estimates for models of social network data that include variables to characterize dyadic nonindependence. While the pseudolikelihood method has been used recently to estimate parameters for such models, the issue of estimating their standard errors, or the variance-covariance matrix more generally, has been neglected. This article addresses the issue by proposing a method for such estimation and also presents an illustrative application of the method to empirical social network data

Covariance · Covariance matrix · Econometrics · Economics · Estimation · Statistics · Variance (accounting · Complex Network Analysis Techniques · Computer Science · Mathematics · Opinion Dynamics and Social Influence · Spatial and Panel Data Analysis

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Obras citantes distintas2
Citas por año0,09
Intervalo de citas2004 - 2023 (20)
Velocidad de citaciónhistorical
Altamente citadoNo
Tipos de citaNeutras: 2
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