We propose a Mahalanobis distance–based Monte Carlo goodness of fit testing procedure for the family of stochastic actor-oriented models for social network evolution. A modified model distance estimator is proposed to help the researcher identify model extensions that will remediate poor fit. A limited simulation study is provided to establish baseline legitimacy for the Mahalanobis distance–based Monte Carlo test and modified model distance estimator. A forward model selection workflow is proposed, and this procedure is demonstrated on a real data set
Also can be found at https://ideas.repec.org/p/adl/wpaper/2017-02.htmlThis paper illustrates how sto...
We present a systematic examination of real network datasets using maximum likelihood estimation for...
Logistic models for random graphs are commonly used to study binary networks when covariate informat...
We propose a Mahalanobis distance–based Monte Carlo goodness of fit testing procedure for the family...
The study of social network dynamics has become an increasingly important component of many discipli...
Modeling the processes underlying social network and attribute change allows researchers to better i...
Stochastic actor-oriented models (SAOMs) can be used to analyse dynamic network data, collected by o...
This paper explores time heterogeneity in stochastic actor oriented models (SAOM) proposed by Snijde...
This paper explores time heterogeneity in stochastic actor oriented models (SAOM) proposed by Snijde...
Social networks and the attributes of the actors in these networks are not static; they may develop ...
One often develops stochastic ecologic simulation models based on local interactions between individ...
We perform a systematic analysis of the quality of fit of the stochastic block model (SBM) for 275 e...
The stochastic actor-oriented model (SAOM) is the most established model for the statistical analysi...
This article discusses the stochastic actor-oriented model for analyzing panel data of networks. The...
Also can be found at https://ideas.repec.org/p/adl/wpaper/2017-02.htmlThis paper illustrates how sto...
We present a systematic examination of real network datasets using maximum likelihood estimation for...
Logistic models for random graphs are commonly used to study binary networks when covariate informat...
We propose a Mahalanobis distance–based Monte Carlo goodness of fit testing procedure for the family...
The study of social network dynamics has become an increasingly important component of many discipli...
Modeling the processes underlying social network and attribute change allows researchers to better i...
Stochastic actor-oriented models (SAOMs) can be used to analyse dynamic network data, collected by o...
This paper explores time heterogeneity in stochastic actor oriented models (SAOM) proposed by Snijde...
This paper explores time heterogeneity in stochastic actor oriented models (SAOM) proposed by Snijde...
Social networks and the attributes of the actors in these networks are not static; they may develop ...
One often develops stochastic ecologic simulation models based on local interactions between individ...
We perform a systematic analysis of the quality of fit of the stochastic block model (SBM) for 275 e...
The stochastic actor-oriented model (SAOM) is the most established model for the statistical analysi...
This article discusses the stochastic actor-oriented model for analyzing panel data of networks. The...
Also can be found at https://ideas.repec.org/p/adl/wpaper/2017-02.htmlThis paper illustrates how sto...
We present a systematic examination of real network datasets using maximum likelihood estimation for...
Logistic models for random graphs are commonly used to study binary networks when covariate informat...