Work

Modeling of networked populations when data is sampled or missing

Year: 2023

Type: article

Source: METRON

DOI: 10.1007/s40300-023-00246-3

Authors: Ian E. Fellows, Mark S. Handcock

Institution: University of California, Los Angeles

Language: English

Topic: Complex Network Analysis Techniques

Subfield: Statistical and Nonlinear Physics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: bronze

Funders: National Science Foundation, Directorate for Computer and Information Science and Engineering, Directorate for Social, Behavioral and Economic Sciences, National Institute of Child Health and Human Development, Eunice Kennedy Shriver National Institute of Child Health and Human Development

Awards: G1216408729, G1793177537, G3973853475, Innovations in Network Modeling for HIV Prevention Studies, Scalable Model-Based Inference for Social Networks from Complex Sampling Designs, G462488941, BIGDATA: Collaborative Research: IA: Population Reproduction of Poverty at Birth from Surveys, Censuses, and Birth Registrations, G595052773, Statistical Methods for Respondent Driven Sampling Data, Maryland Population Research Center, California Center for Population Research (CCPR) at UCLA

OpenAlex ID: W4377140337

FWCI: 0.298

Cites: 21

Cited by: 4

Related to: 10