Missing data on network ties is a fundamental problem for network analyses. The biases induced by... more Missing data on network ties is a fundamental problem for network analyses. The biases induced by missing edge data, even when missing completely at random (MCAR), are widely acknowledged (Kossinets, 2006; Huisman & Steglich, 2008; Huisman, 2009). Although model based techniques for missing network data are quite promising, they are not available for all analyses (Koskinen, Robins & Pattison, 2010). Multiple imputation for network data is able to overcome this problem. This study expands on recent work on multiple imputation of missing data in networks with extensive simulations (Wang et al. 2016). Different models for imputing the missing data are compared under 64 conditions
u recenti modelli statistici e metodi di stima per l'analisi longitudinale di reti sociali. ... more u recenti modelli statistici e metodi di stima per l'analisi longitudinale di reti sociali. Per rappresentare i processi sottostanti le dinamiche di rete, ` e utile pensare ai dati di panel come ad osservazioni provenienti da un processo a tempo continuo definito sullo spazio dei grafi orientati. Vengono discussi e illustrati modelli stocastici tie-oriented e actor-oriented in grado di riflettere sia dinamiche endogene che effetti di variabili esogene. Tali modelli non consentono il calcolo esplicito ma possono essere sviluppati specifici schemi di simulazione. Sono inoltre proposti metodi di approssimazione stocastica per la stima dei parametri. Un esempio di applicazione di questi modelli ` e condotto sui dati reticolari provenienti da uno studio sul precursore della comunicazione via e-mail.
A recurrent problem in the analysis of behavioral dynamics, given a simultaneously evolving socia... more A recurrent problem in the analysis of behavioral dynamics, given a simultaneously evolving social network, is the difficulty of separating the effects of partner selection from the effects of social influence. Because misattribution of selection effects to social influence, or vice versa, suggests wrong conclusions about the social mechanisms underlying the observed dynamics, special diligence in data analysis is advisable. While a dependable and validmethod would benefit several research areas, according to the best of our knowledge, it has been lacking in the extant literature. In this paper, we present a recently developed family of statistical models that enables researchers to separate the two effects in a statistically adequate manner. To illustrate our method, we investigate the roles of homophile selection and peer influence mechanisms in the joint dynamics of friendship formation and substance use among adolescents. Making use of a three-wave panel measured in the years 19...
Stochastic actor-based models for network dynamics have the primary aim of statistical inference ... more Stochastic actor-based models for network dynamics have the primary aim of statistical inference about processes of network change, but may be regarded as a kind of agent-based models. Similar to many other agent-based models, they are based on local rules for actor behavior. Different from many other agent-based models, by including elements of generalized linear statistical models they aim to be realistic detailed representations of network dynamics in empirical data sets. Statistical parallels to micro–macro considerations can be found in the estimation of parameters determining local actor behavior from empirical data, and the assessment of goodness of fit from the correspondence with network-level descriptives. This article studies several network-level consequences of dynamic actor-based models applied to represent cross-sectional network data. Two examples illustrate how network-level characteristics can be obtained as emergent features implied by microspecifications of actor...
effects of risk taking behavior on network dynamics. test effects of network embeddedness on the ... more effects of risk taking behavior on network dynamics. test effects of network embeddedness on the dynamics of risk taking behavior, and taking behavior, measured in the years 1995-97 at a school in Scotland, we simultaneously smoking and drinking. Making use of a three-wave panel of friendship networks and risk play in the dynamics of friendship formation and risk taking behavior in the shape of an illustrative example, we investigate the role which selection and influence mechanisms statistical models that in principle allows for a separation of the two types of effects. As interventions will affect the dynamics of interest. In this paper, we propose a family of versa, may lead to incorrect explanations and wrong conclusions about how potential effects of social influence. Misattribution of selection effects to social influence, or vice evolving social network, is the difficulty of separating effects of partner selection from A recurrent problem in the analysis of behavioral dynamics, given a simultaneously 1 adolescents. It is by now well-established that smoking, alcohol and drug use tend to be
Multilevel Network Analysis for the Social Sciences, 2015
Multilevel analysis and social network analysis both represent social structure, and have led to ... more Multilevel analysis and social network analysis both represent social structure, and have led to statistical methodologies departing from the traditional atomic approach to social systems that is implied by linear regression analysis. There are various ways in which multilevel considerations are important for social network analysis. This chapter starts by sketching the importance of multilevel issues for traditional social network analysis, and briefly reviewing multilevel analysis and statistical models for social networks. It continues by treating multilevel network analysis, defined as network analysis in multiple ‘parallel’ groups, which is important for gauging the variability between such groups and for the generalizability of results. Finally, a new development is discussed: the analysis of multilevel networks, defined as networks including several node sets of different kinds, where the nature of ties differs according to the kind of nodes they connect.
Bulletin de Méthodologie Sociologique, 2002
Multi-Level Analysis. This article is based on a one-day course that the author has presented in ... more Multi-Level Analysis. This article is based on a one-day course that the author has presented in Lille and in Paris to French-speaking sociologists who are just now becoming familiar with the method.
Missing data on network ties is a fundamental problem for network analyses. The biases induced by... more Missing data on network ties is a fundamental problem for network analyses. The biases induced by missing edge data, even when missing completely at random (MCAR), are widely acknowledged (Kossinets, 2006; Huisman & Steglich, 2008; Huisman, 2009). Although model based techniques for missing network data are quite promising, they are not available for all analyses (Koskinen, Robins & Pattison, 2010). Multiple imputation for network data is able to overcome this problem. This study expands on recent work on multiple imputation of missing data in networks with extensive simulations (Wang et al. 2016). Different models for imputing the missing data are compared under 64 conditions
u recenti modelli statistici e metodi di stima per l'analisi longitudinale di reti sociali. ... more u recenti modelli statistici e metodi di stima per l'analisi longitudinale di reti sociali. Per rappresentare i processi sottostanti le dinamiche di rete, ` e utile pensare ai dati di panel come ad osservazioni provenienti da un processo a tempo continuo definito sullo spazio dei grafi orientati. Vengono discussi e illustrati modelli stocastici tie-oriented e actor-oriented in grado di riflettere sia dinamiche endogene che effetti di variabili esogene. Tali modelli non consentono il calcolo esplicito ma possono essere sviluppati specifici schemi di simulazione. Sono inoltre proposti metodi di approssimazione stocastica per la stima dei parametri. Un esempio di applicazione di questi modelli ` e condotto sui dati reticolari provenienti da uno studio sul precursore della comunicazione via e-mail.
A recurrent problem in the analysis of behavioral dynamics, given a simultaneously evolving socia... more A recurrent problem in the analysis of behavioral dynamics, given a simultaneously evolving social network, is the difficulty of separating the effects of partner selection from the effects of social influence. Because misattribution of selection effects to social influence, or vice versa, suggests wrong conclusions about the social mechanisms underlying the observed dynamics, special diligence in data analysis is advisable. While a dependable and validmethod would benefit several research areas, according to the best of our knowledge, it has been lacking in the extant literature. In this paper, we present a recently developed family of statistical models that enables researchers to separate the two effects in a statistically adequate manner. To illustrate our method, we investigate the roles of homophile selection and peer influence mechanisms in the joint dynamics of friendship formation and substance use among adolescents. Making use of a three-wave panel measured in the years 19...
Stochastic actor-based models for network dynamics have the primary aim of statistical inference ... more Stochastic actor-based models for network dynamics have the primary aim of statistical inference about processes of network change, but may be regarded as a kind of agent-based models. Similar to many other agent-based models, they are based on local rules for actor behavior. Different from many other agent-based models, by including elements of generalized linear statistical models they aim to be realistic detailed representations of network dynamics in empirical data sets. Statistical parallels to micro–macro considerations can be found in the estimation of parameters determining local actor behavior from empirical data, and the assessment of goodness of fit from the correspondence with network-level descriptives. This article studies several network-level consequences of dynamic actor-based models applied to represent cross-sectional network data. Two examples illustrate how network-level characteristics can be obtained as emergent features implied by microspecifications of actor...
effects of risk taking behavior on network dynamics. test effects of network embeddedness on the ... more effects of risk taking behavior on network dynamics. test effects of network embeddedness on the dynamics of risk taking behavior, and taking behavior, measured in the years 1995-97 at a school in Scotland, we simultaneously smoking and drinking. Making use of a three-wave panel of friendship networks and risk play in the dynamics of friendship formation and risk taking behavior in the shape of an illustrative example, we investigate the role which selection and influence mechanisms statistical models that in principle allows for a separation of the two types of effects. As interventions will affect the dynamics of interest. In this paper, we propose a family of versa, may lead to incorrect explanations and wrong conclusions about how potential effects of social influence. Misattribution of selection effects to social influence, or vice evolving social network, is the difficulty of separating effects of partner selection from A recurrent problem in the analysis of behavioral dynamics, given a simultaneously 1 adolescents. It is by now well-established that smoking, alcohol and drug use tend to be
Multilevel Network Analysis for the Social Sciences, 2015
Multilevel analysis and social network analysis both represent social structure, and have led to ... more Multilevel analysis and social network analysis both represent social structure, and have led to statistical methodologies departing from the traditional atomic approach to social systems that is implied by linear regression analysis. There are various ways in which multilevel considerations are important for social network analysis. This chapter starts by sketching the importance of multilevel issues for traditional social network analysis, and briefly reviewing multilevel analysis and statistical models for social networks. It continues by treating multilevel network analysis, defined as network analysis in multiple ‘parallel’ groups, which is important for gauging the variability between such groups and for the generalizability of results. Finally, a new development is discussed: the analysis of multilevel networks, defined as networks including several node sets of different kinds, where the nature of ties differs according to the kind of nodes they connect.
Bulletin de Méthodologie Sociologique, 2002
Multi-Level Analysis. This article is based on a one-day course that the author has presented in ... more Multi-Level Analysis. This article is based on a one-day course that the author has presented in Lille and in Paris to French-speaking sociologists who are just now becoming familiar with the method.
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