Journal ArticleDOI
Sequential Social Network Data.
Stanley Wasserman,Dawn Iacobucci +1 more
TLDR
A new method is proposed for the statistical analysis of dyadic social interaction data measured over time based on loglinear models for the probabilities for various dyad (or actor pair) states and generalizes the statistical methods proposed by Holland and Leinhardt (1981), Fienberg, Meyer, & Wasserman (1985), and Wasserman (1987) for social network data.Abstract:
A new method is proposed for the statistical analysis of dyadic social interaction data measured over time. The data to be studied are assumed to be realizations of a social network of a fixed set of actors interacting on a single relation. The method is based on loglinear models for the probabilities for various dyad (or actor pair) states and generalizes the statistical methods proposed by Holland and Leinhardt (1981), Fienberg, Meyer, & Wasserman (1985), and Wasserman (1987) for social network data. Two statistical models are described: the first is an “associative” approach that allows for the study of how the network has changed over time; the second is a “predictive” approach that permits the researcher to model one time point as a function of previous time points. These approaches are briefly contrasted with earlier methods for the sequential analysis of social networks and are illustrated with an example of longitudinal sociometric data.read more
Citations
More filters
Journal ArticleDOI
Introduction to stochastic actor-based models for network dynamics
TL;DR: Stochastic actor-based models as discussed by the authors are models for network dynamics that can represent a wide variety of influences on network change, and allow to estimate parameters expressing such influences, and test corresponding hypotheses.
Journal ArticleDOI
The statistical evaluation of social network dynamics
TL;DR: A class of statistical models is proposed for longitudinal network data that are continuous-time Markov chain models that can be implemented as simulation models and statistical procedures are proposed that are based on the method of moments.
Journal ArticleDOI
The Misalignment of Product Architecture and Organizational Structure in Complex Product Development
TL;DR: This research investigates how organizational and system boundaries, design interface strength, indirect interactions, and system modularity impact the alignment of design interfaces and team interactions and shows how boundary effects moderate the impact of design Interface strength and indirect team interactions,and are contingent on system modularities.
Book ChapterDOI
Models for longitudinal network datain
TL;DR: This chapter treats statistical methods for network evolution with a focus on models where a continuous-time network evolution is assumed although the observations are made at discrete time points.
Journal ArticleDOI
A p* primer: logit models for social networks
TL;DR: This paper is a primer on how to use these important breakthroughs to model the relationships between actors within a single network and provides an extension of the models to multiple networks.
References
More filters
Book
Discrete multivariate analysis: theory and practice
TL;DR: Discrete Multivariate Analysis is a comprehensive text and general reference on the analysis of discrete multivariate data, particularly in the form of multidimensional tables, and contains a wealth of material on important topics.
Book
The analysis of cross-classified categorical data
TL;DR: The second edition has been updated and revised, with more emphasis on logic and logistic response properties and on the small-sample behavior of chi-square statistics as mentioned in this paper, and includes 40 to 50 new problems with most having separate data sheets.
Book
Analysis of ordinal categorical data
TL;DR: In this article, the authors present a survey of the advantages of using logit models in regression models for Ordinal Probabilities, Scores, and Odds Ratios, as well as their drawbacks.
Journal ArticleDOI
An Exponential Family of Probability Distributions for Directed Graphs
Paul W. Holland,Samuel Leinhardt +1 more
TL;DR: An exponential family of distributions that can be used for analyzing directed graph data is described, and several special cases are discussed along with some possible substantive interpretations.