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Contemporaneous Statistics for Estimation in Stochastic Actor-Oriented Co-evolution Models

Published online by Cambridge University Press:  01 January 2025

Viviana Amati Open the ORCID record for Viviana Amati [Opens in a new window] ,
Felix Schönenberger  and
Tom A. B. Snijders Open the ORCID record for Tom A. B. Snijders [Opens in a new window]
Viviana Amati*
Affiliation:
ETH Zurich
Felix Schönenberger
Affiliation:
ETH Zurich
Tom A. B. Snijders
Affiliation:
University of Groningen University of Oxford
*
Correspondence should be made to Viviana Amati, Social Networks Lab, Department of Humanities, Social and Political Sciences, ETH Zurich, Weinbergstrasse 109, 8092 Zurich, Switzerland. Email:viviana.amati@gess.ethz.ch
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Abstract

Stochastic actor-oriented models (SAOMs) can be used to analyse dynamic network data, collected by observing a network and a behaviour in a panel design. The parameters of SAOMs are usually estimated by the method of moments (MoM) implemented by a stochastic approximation algorithm, where statistics defining the moment conditions correspond in a natural way to the parameters. Here, we propose to apply the generalized method of moments (GMoM), using more statistics than parameters. We concentrate on statistics depending jointly on the network and the behaviour, because of the importance of their interdependence, and propose to add contemporaneous statistics to the usual cross-lagged statistics. We describe the stochastic algorithm developed to approximate the GMoM solution. A small simulation study supports the greater statistical efficiency of the GMoM estimator compared to the MoM.

Keywords

generalized method of momentsnetworksbehaviourpanel datastochastic actor-oriented modelstochastic approximation
Type
Original Paper
Information
Psychometrika , Volume 84 , Issue 4 , December 2019 , pp. 1068 - 1096
Copyright
Copyright © 2019 The Psychometric Society

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