Tom A B Snijders
Biographic Data
| ID | 3976247 |
|---|---|
| NAME | Tom A B Snijders |
| GIVEN NAMES | Tom A B |
| FAMILY NAME | Snijders |
| SIGNATURE | SNIJDERS T A B |
| AFFILIATIONS | University of Groningen |
| VERIFIED | No |
| TOTAL WORKS | 44 |
| TOTAL CITATIONS | 483 |
| AUTHOR COUNT | 43 |
| EDITOR COUNT | 1 |
| FIRST PUBLICATION YEAR | 1987 |
| LATEST PUBLICATION YEAR | 2020 |
| H-INDEX | 10 |
The Dynamics of Interethnic Friendships and Negative Ties in Secondary School: The Role of Peer-Perceived Ethnicity
This study examines ethnic integration in secondary school. Social identity theory suggests that perception of relevant individual attributes plays a crucial role in defining ingroups and outgroups, contributing to befriending, and disliking others. Therefore, we analyze the role of peer-perceived ethnicity in social ties. Networks of friendship, dislike, and perceived ethnicity were modeled together using dynamic stochastic actor-oriented models…
Statistical Power in Longitudinal Network Studies
Longitudinal social network studies can easily suffer from insufficient statistical power. Studies that simultaneously investigate change of network ties and change of nodal attributes (selection and influence studies) are particularly at risk because the number of nodal observations is typically much lower than the number of observed tie variables. This article presents a simulation-based procedure to evaluate statistical power of longitudinal s…
Beyond homophily: Incorporating actor variables in statistical network models
We consider the specification of effects of numerical actor attributes, having an interval level of measurement, in statistical models for directed social networks. A fundamental mechanism is homophily or assortativity, where actors have a higher likelihood to be tied with others having similar values of the variable under study. But there are other mechanisms that may also play a role in how the attribute values of two actors influence the likel…
Forms of Dependence: Comparing Saoms and ERGMs From Basic Principles
Two approaches for the statistical analysis of social network generation are widely used; the tie-oriented exponential random graph model (ERGM) and the stochastic actor-oriented model (SAOM) or Siena model. While the choice for either model by empirical researchers often seems arbitrary, there are important differences between these models that current literature tends to miss. First, the ERGM is defined on the graph level, while the SAOM is def…
Multivariate dynamics of one-mode and two-mode networks: Explaining similarity in sports participation among friends
We examined social mechanisms that account for similarity in the social context of school-sponsored extracurricular sports activities among friends. We distinguish two social mechanisms: “shared sports activities that lead to friendship,” whereby friendship formation and maintenance are conditioned by joint sports participation, and “friendship that leads to shared sports activities,” a form of social influence whereby adolescents join or maintai…
Stochastic Actor-Oriented Models for Network Dynamics
This article discusses the stochastic actor-oriented model for analyzing panel data of networks. The model is defined as a continuous-time Markov chain, observed at two or more discrete time moments. It can be regarded as a generalized linear model with a large amount of missing data. Several estimation methods are discussed. After presenting the model for evolution of networks, attention is given to coevolution models. These use the same approac…
Stochastic Actor Oriented Models for Network Dynamics
Stochastic Actor Oriented Models for Network Dynamics are used for the statistical analysis of longitudinal network data collected as a panel. The probability model defines an unobserved stochastic process of tie changes, where social actors add new ties or drop existing ties in response to the current network structure; the panel observations are snapshots of the resulting changing network. The statistical analysis is based on computer simulatio…
Popularity breeds contempt: The evolution of reputational dislike relations and friendships in high school
Multilevel Network Analysis for the Social Sciences: Theory, Methods and Applications
Representing Micro-Macro Linkages by Actor-based Dynamic Network Models
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 dyn…
Siena: Statistical Modeling of Longitudinal Network Data
Network Dynamics
In Search of Value Added in the Case of Complex School Effects
In traditional studies on value-added indicators of educational effectiveness, students are usually treated as belonging to those schools where they took their final examination. However, in practice, students sometimes attend multiple schools and therefore it is questionable whether this assumption of belonging to the last school they attended can be made. Furthermore, the schools attended earlier by students might have long-term effects on thei…
A model for the multiplex dynamics of two-mode and one-mode networks, with an application to employment preference, friendship, and advice
Introduction to the special issue on Network Dynamics (Part 2)
A Hierarchy of Preferences: A Longitudinal Network Analysis Approach to PTA Formation
Bilateral trade agreements have proliferated rapidly within the last two decades, growing into a dense network of multiple ties between countries. The spread of preferential trade agreements (PTAs), however, is not uniform: some countries have signed a multitude of deals, while others remain much less involved. This article presents a longitudinal network analysis method to analyze the patterns of the formation of trade agreements, based on the m…
Multilevel Analysis
Statistical Models for Social Networks
Statistical models for social networks as dependent variables must represent the typical network dependencies between tie variables such as reciprocity, homophily, transitivity, etc. This review first treats models for single (cross-sectionally observed) networks and then for network dynamics. For single networks, the older literature concentrated on conditionally uniform models. Various types of latent space models have been developed: for discr…
Introduction to stochastic actor-based models for network dynamics
Conditional Marginalization for Exponential Random Graph Models
For exponential random graph models, under quite general conditions, it is proved that induced subgraphs on node sets disconnected from the other nodes still have distributions from an exponential random graph model. This can help in the theoretical interpretation of such models. An application is that for saturated snowball samples from a potentially larger graph which is a realization of an exponential random graph model, it is possible to do t…
Sensitivity of MRQAP Tests to Collinearity and Autocorrelation Conditions
Multiple regression quadratic assignment procedures (MRQAP) tests are permutation tests for multiple linear regression model coefficients for data organized in square matrices of relatedness among n objects. Such a data structure is typical in social network studies, where variables indicate some type of relation between a given set of actors. We present a new permutation method (called “double semi-partialing”, or DSP) that complements the famil…
Beyond dyadic interdependence: Actor-oriented models for co-evolving social networks and individual behaviors
Actor-oriented models are described as a longitudinal strategy for examining the co-evolution of social networks and individual behaviors. We argue that these models provide advantages over conventional approaches due to their ability to account for inherent dependencies between individuals embedded in a social network (i.e., reciprocity, transitivity) and model interdependencies between network and behavioral dynamics. We provide a brief explana…
A comparison of various approaches to the exponential random graph model: A reanalysis of 102 student networks in school classes
Evaluation of the chronic disease self-management program (CDSMP) among chronically ill older people in the Netherlands
Applying Siena
We give a nontechnical introduction into recently developed methods for analyzing the coevolution of social networks and behavior(s) of the network actors. This coevolution is crucial for a variety of research topics that currently receive a lot of attention, such as the role of peer groups in adolescent development. A family of dynamic actor-driven models for the coevolution process is sketched, and it is shown how to use the SIENA software for …
Stochastic actor-oriented models for network change
A class of models is proposed for longitudinal network data. These models are along the lines of methodological individualism: actors use heuristics to try to achieve their individual goals, subject to constraints. The current network structure is among these constraints. The models are continuous time Markov chain models that can be implemented as simulation models. They incorporate random change in addition to the purposeful change that follows…
Statistical Models for Social Networks
Statistical models for social networks as dependent variables must represent the typical network dependencies between tie variables such as reciprocity, homophily, transitivity, etc. This review first treats models for single (cross-sectionally observed) networks and then for network dynamics. For single networks, the older literature concentrated on conditionally uniform models. Various types of latent space models have been developed: for discr…
Modeled Variance in Two-Level Models
The concept of explained proportion of variance or modeled proportion of variance is reviewed in the situation of the random effects hierarchical two-level model. It is argued that the proportional reduction in (estimated) variance components is not an attractive parameter to represent the joint importance of the explanatory (independent) variables for modeling the dependent variable. It is preferable instead to work with the proportional reducti…
Statistical Analysis of Longitudinal Network Data With Changing Composition
Markov chains can be used for the modeling of complex longitudinal network data. One class of probability models to model the evolution of social networks are stochastic actor-oriented models for network change proposed by Snijders. These models are continuous-time Markov chain models that are implemented as simulation models. The authors propose an extension of the simulation algorithm of stochastic actor-oriented models to include networks of c…
Representing Micro-Macro Linkages by Actor-based Dynamic Network Models
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 dyn…
A Hierarchy of Preferences: A Longitudinal Network Analysis Approach to PTA Formation
Bilateral trade agreements have proliferated rapidly within the last two decades, growing into a dense network of multiple ties between countries. The spread of preferential trade agreements (PTAs), however, is not uniform: some countries have signed a multitude of deals, while others remain much less involved. This article presents a longitudinal network analysis method to analyze the patterns of the formation of trade agreements, based on the m…
Prologue to the Measurement of Social Capital
Social capital has become quite a popular concept in the sociological and economic literature, and even in the general press. Scientific investigations using this concept have measured it, however, usually in rather ad hoc fashions. In this paper I discuss possible approaches that could be followed to measure the social capital of individuals. What kind of questions should be posed to the individual, and how should these questions be aggregated t…
Beyond homophily: Incorporating actor variables in statistical network models
We consider the specification of effects of numerical actor attributes, having an interval level of measurement, in statistical models for directed social networks. A fundamental mechanism is homophily or assortativity, where actors have a higher likelihood to be tied with others having similar values of the variable under study. But there are other mechanisms that may also play a role in how the attribute values of two actors influence the likel…
Forms of Dependence: Comparing Saoms and ERGMs From Basic Principles
Two approaches for the statistical analysis of social network generation are widely used; the tie-oriented exponential random graph model (ERGM) and the stochastic actor-oriented model (SAOM) or Siena model. While the choice for either model by empirical researchers often seems arbitrary, there are important differences between these models that current literature tends to miss. First, the ERGM is defined on the graph level, while the SAOM is def…
Multivariate dynamics of one-mode and two-mode networks: Explaining similarity in sports participation among friends
We examined social mechanisms that account for similarity in the social context of school-sponsored extracurricular sports activities among friends. We distinguish two social mechanisms: “shared sports activities that lead to friendship,” whereby friendship formation and maintenance are conditioned by joint sports participation, and “friendship that leads to shared sports activities,” a form of social influence whereby adolescents join or maintai…
Do personal conditions and circumstances surrounding partner loss explain loneliness in newly bereaved older adults
This longitudinal study aims to explain loneliness in newly bereaved older adults, taking into account personal and circumstantial conditions surrounding the partner's death. A distinction is made between emotional and social loneliness. Data were gathered both before and after partner loss. Results were interpreted within the framework of the Theory of Mental Incongruity. The findings reveal that being unable to anticipate the partner's death is…
Conditional Marginalization for Exponential Random Graph Models
For exponential random graph models, under quite general conditions, it is proved that induced subgraphs on node sets disconnected from the other nodes still have distributions from an exponential random graph model. This can help in the theoretical interpretation of such models. An application is that for saturated snowball samples from a potentially larger graph which is a realization of an exponential random graph model, it is possible to do t…
Statistical Power in Longitudinal Network Studies
Longitudinal social network studies can easily suffer from insufficient statistical power. Studies that simultaneously investigate change of network ties and change of nodal attributes (selection and influence studies) are particularly at risk because the number of nodal observations is typically much lower than the number of observed tie variables. This article presents a simulation-based procedure to evaluate statistical power of longitudinal s…
The Dynamics of Interethnic Friendships and Negative Ties in Secondary School: The Role of Peer-Perceived Ethnicity
This study examines ethnic integration in secondary school. Social identity theory suggests that perception of relevant individual attributes plays a crucial role in defining ingroups and outgroups, contributing to befriending, and disliking others. Therefore, we analyze the role of peer-perceived ethnicity in social ties. Networks of friendship, dislike, and perceived ethnicity were modeled together using dynamic stochastic actor-oriented models…
Evaluation of the chronic disease self-management program (CDSMP) among chronically ill older people in the Netherlands
Extensions of triad counts to networks with different subsets of points and testing underlying random graph distributions
Testing for change in a digraph at two time points
Standard Errors and Sample Sizes for Two-Level Research
The hierarchical linear model approach to a two-level design is considered, some variables at the lower level having fixed and others having random regression coefficients. An approximation is derived to the covariance matrix of the estimators of the fixed regression coefficients (for variables at the lower and the higher level) under the assumption that the sample sizes at either level are large enough. This covariance matrix is expressed as a f…
Modeled Variance in Two-Level Models
The concept of explained proportion of variance or modeled proportion of variance is reviewed in the situation of the random effects hierarchical two-level model. It is argued that the proportional reduction in (estimated) variance components is not an attractive parameter to represent the joint importance of the explanatory (independent) variables for modeling the dependent variable. It is preferable instead to work with the proportional reducti…
Stochastic actor-oriented models for network change
A class of models is proposed for longitudinal network data. These models are along the lines of methodological individualism: actors use heuristics to try to achieve their individual goals, subject to constraints. The current network structure is among these constraints. The models are continuous time Markov chain models that can be implemented as simulation models. They incorporate random change in addition to the purposeful change that follows…
Parameters in collective decision making models: Estimation and sensitivity
Simulation models for collective decision making are based on theoretical and empirical insight in the decision making process, but still contain a number of parameters of which the values are determined ad hoc. For the dynamic access model, some of such parameters are discussed, and it is proposed to extend the utility functions with a random term of which the variance also is an unknown parameter. These parameters can be estimated by fitting mo…
Controlling for size in centrality scores
Friendship Networks Through Time: An Actor-Oriented Dynamic Statistical Network Model
The social relations model for family data: A multilevel approach
Multilevel models are proposed to study relational or dyadic data from multiple persons in families or other groups. The variable under study is assumed to refer to a dyadic relation between individuals in the groups. The proposed models are elaborations of the Social Relations Model. The different roles of father, mother, and child are emphasized in these models. Multilevel models provide researchers with a method to estimate the variances and c…
Do personal conditions and circumstances surrounding partner loss explain loneliness in newly bereaved older adults
This longitudinal study aims to explain loneliness in newly bereaved older adults, taking into account personal and circumstantial conditions surrounding the partner's death. A distinction is made between emotional and social loneliness. Data were gathered both before and after partner loss. Results were interpreted within the framework of the Theory of Mental Incongruity. The findings reveal that being unable to anticipate the partner's death is…
Prologue to the Measurement of Social Capital
Social capital has become quite a popular concept in the sociological and economic literature, and even in the general press. Scientific investigations using this concept have measured it, however, usually in rather ad hoc fashions. In this paper I discuss possible approaches that could be followed to measure the social capital of individuals. What kind of questions should be posed to the individual, and how should these questions be aggregated t…
Estimation and Prediction for Stochastic Blockstructures
A statistical approach to a posteriori blockmodeling for digraphs and valued digraphs is proposed. The probability model assumes that the vertices of the digraph are partitioned into several unobserved (latent) classes and that the probability distribution of the relation between two vertices depends only on the classes to which they belong. A Bayesian estimator based on Gibbs sampling is proposed. The basic model is not identified, because class…
Lonely but Not Alone: Emotional Isolation and Social Isolation as Two Distinct Dimensions of Loneliness in Older People
The unidimensional nature of the De Jong-Gierveld Loneliness Scale is investigated. The internal properties of the scale scores were studied using item response theory, supplemented by an external validity study. In line with the theory of relational loneliness, the results stress the significance of distinguishing between emotional loneliness and social loneliness
Guest Editors' Introduction to the Special Issue on Causality at Work
Statistical Analysis of Longitudinal Network Data With Changing Composition
Markov chains can be used for the modeling of complex longitudinal network data. One class of probability models to model the evolution of social networks are stochastic actor-oriented models for network change proposed by Snijders. These models are continuous-time Markov chain models that are implemented as simulation models. The authors propose an extension of the simulation algorithm of stochastic actor-oriented models to include networks of c…
Explained Variation in dynamic network models
A measure for explained variation is proposed for stochastic actor-driven models for data on social networks. The measure is based on the entropy of the distribution of the choices made by the actors during the network evolution process. This measure can be helpful in the specification and interpretation of statistical models for longitudinal network data
Power and Sample Size in Multilevel Linear Models
Sample size determination in multilevel designs requires attention to the fact that statistical power depends on the total sample sizes for each level. It is usually desirable to have as many units as possible at the top level of the multilevel hierarchy. Some formulas are given to obtain insight in the design aspects that are most influential for standard errors and power.
Models for Longitudinal Network Data
This chapter treats statistical methods for network evolution. It is argued that it is most fruitful to consider models where network evolution is represented as the result of many (usually nonobserved) small changes occurring between the consecutively observed networks. Accordingly, the focus is on models where a continuous-time network evolution is assumed, although the observations are made at discrete time points (two or more). Three models a…
The Resource Generator: Social capital quantification with concrete items
Applying Siena
We give a nontechnical introduction into recently developed methods for analyzing the coevolution of social networks and behavior(s) of the network actors. This coevolution is crucial for a variety of research topics that currently receive a lot of attention, such as the role of peer groups in adolescent development. A family of dynamic actor-driven models for the coevolution process is sketched, and it is shown how to use the SIENA software for …
Sensitivity of MRQAP Tests to Collinearity and Autocorrelation Conditions
Multiple regression quadratic assignment procedures (MRQAP) tests are permutation tests for multiple linear regression model coefficients for data organized in square matrices of relatedness among n objects. Such a data structure is typical in social network studies, where variables indicate some type of relation between a given set of actors. We present a new permutation method (called “double semi-partialing”, or DSP) that complements the famil…
Beyond dyadic interdependence: Actor-oriented models for co-evolving social networks and individual behaviors
Actor-oriented models are described as a longitudinal strategy for examining the co-evolution of social networks and individual behaviors. We argue that these models provide advantages over conventional approaches due to their ability to account for inherent dependencies between individuals embedded in a social network (i.e., reciprocity, transitivity) and model interdependencies between network and behavioral dynamics. We provide a brief explana…
A comparison of various approaches to the exponential random graph model: A reanalysis of 102 student networks in school classes
Evaluation of the chronic disease self-management program (CDSMP) among chronically ill older people in the Netherlands
Introduction to stochastic actor-based models for network dynamics
Computer Science (31 works) · Complex Network Analysis Techniques (23 works) · Mathematics (23 works) · Opinion Dynamics and Social Influence (20 works) · Statistics (17 works) · Psychology (15 works) · Econometrics (13 works) · Social Capital and Networks (12 works) · Social Psychology (11 works) · Data mining (10 works)