Using retrospective sampling to estimate models of relationship status in large longitudinal social networks

DOI10.1016/J.CSDA.2014.08.001OpenAlexW1983402764WikidataQ40182781 ScholiaQ40182781MaRDI QIDQ1623738

Sudeshna Paul, A. James O'Malley

Publication date: 23 November 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc4673682

zbMATH Keywords

longitudinalsocial networkconditional independencesparse dataweightingretrospective samplingsociocentric design

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Social networks; opinion dynamics (91D30) Applications of statistics to social sciences (62P25) Sampling theory, sample surveys (62D05)

Related Items (1)

A particle-learning-based approach to estimate the influence matrix of online social networks

Cites Work

• Logit models and logistic regressions for social networks. I: An introduction to Markov graphs and \(p^*\)
• Bayesian and likelihood methods for fitting multilevel models with complex level-1 variation.
• Markov Graphs
• Weighting for Unequal Selection Probabilities in Multilevel Models
• Conditional logistic analysis of case-control studies with complex sampling
• Latent Space Approaches to Social Network Analysis
• p₂: a random effects model with covariates for directed graphs
• Bilinear Mixed-Effects Models for Dyadic Data

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