Systematic Investigation of the Effects of Missing Data on Statistical Models for Networks
Abstract
Many have argued that theoretical perspectives and promising findings from social network analysis are an important influence on contemporary social and behavioral sciences; while at the sametime the current theoretical and empirical convergence across the social and behavioral sciences have strengthened network science. Network studies facilitate direct behavioral intervention by pinpointing how human relationships encourage or discourage attitudes, actions, and behaviors. Social network analysis (SNA) provides important tools for identifying and understanding the social and contextual factors relevant to engagement in particular behaviors.1-4 By quantifying relational information and linking it to human behavior, many important quantitative methods, such as matrix algebra, graph theory and statistical analysis, can be applied to identify structural patterns in social networks andmeasure the association of those patterns with various behavioral outcomes.5.
Document Details
- Document Type
- Technical Report
- Publication Date
- Nov 29, 2016
- Accession Number
- AD1220435
Entities
People
- Harold Green
- Stanley Wasserman
Organizations
- Indiana University