Literature DB >> 31309405

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

Viviana Amati1, Felix Schönenberger2, Tom A B Snijders3,4,5.   

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.

Entities:  

Keywords:  behaviour; generalized method of moments; networks; panel data; stochastic actor-oriented model; stochastic approximation

Mesh:

Year:  2019        PMID: 31309405     DOI: 10.1007/s11336-019-09676-3

Source DB:  PubMed          Journal:  Psychometrika        ISSN: 0033-3123            Impact factor:   2.500


  4 in total

1.  Curved Exponential Family Models for Social Networks.

Authors:  David R Hunter
Journal:  Soc Networks       Date:  2007-03

2.  Gender, Friendship Networks, and Delinquency: A Dynamic Network Approach.

Authors:  Dana L Haynie; Nathan J Doogan; Brian Soller
Journal:  Criminology       Date:  2014-11

3.  MAXIMUM LIKELIHOOD ESTIMATION FOR SOCIAL NETWORK DYNAMICS.

Authors:  Tom A B Snijders; Johan Koskinen; Michael Schweinberger
Journal:  Ann Appl Stat       Date:  2010-06-01       Impact factor: 2.083

4.  Model-implied instrumental variable-generalized method of moments (MIIV-GMM) estimators for latent variable models.

Authors:  Kenneth A Bollen; Stanislav Kolenikov; Shawn Bauldry
Journal:  Psychometrika       Date:  2013-04-11       Impact factor: 2.500

  4 in total

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