ArticleSociological methodology2012
Macrostructure from Microstructure: Generating Whole Systems from Ego Networks.
Article in Sociological methodology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
20 citing papers in PubMed.
- Trial
- Geometric deep learning enables high-fidelity network imputation for HIV transmission modeling.Communications medicine · 2026Article
- Considerations for Social Networks and Health Data Sharing: An Overview.Annals of epidemiology · 2025Review
- Analytic Advances in Social Networks and Health in the Twenty-First Century.Journal of health and social behavior · 2022Review
- Using Social Networks to Sample Migrants and Study the Complexity of Contemporary Immigration: An Evaluation Study.Demography · 2022Article
- Impact of Survey Design on Estimation of Exponential-Family Random Graph Models from Egocentrically-Sampled Data.Social networks · 2022Article
- Network sampling coverage III: Imputation of missing network data under different network and missing data conditions.Social networks · 2022Article
- Review
- Estimating Contextual Effects from Ego Network Data.Sociological methodology · 2020Article
- SOCIAL NETWORKS AND TRANSNATIONAL SOCIAL FIELDS: A REVIEW OF QUANTITATIVE AND MIXED-METHODS APPROACHES.The International migration review · 2020Article
- A survey on exponential random graph models: an application perspective.PeerJ. Computer science · 2020Article
- Sexual Networks of Racially Diverse Young MSM Differ in Racial Homophily But Not Concurrency.Journal of acquired immune deficiency syndromes (1999) · 2018Article
- NEW SURVEY QUESTIONS AND ESTIMATORS FOR NETWORK CLUSTERING WITH RESPONDENT-DRIVEN SAMPLING DATA.Sociological methodology · 2017Article
- INFERENCE FOR SOCIAL NETWORK MODELS FROM EGOCENTRICALLY SAMPLED DATA, WITH APPLICATION TO UNDERSTANDING PERSISTENT RACIAL DISPARITIES IN HIV PREVALENCE IN THE US.The annals of applied statistics · 2017Article
- Network sampling coverage II: The effect of non-random missing data on network measurement.Social networks · 2017Article
- THE GRAPHICAL STRUCTURE OF RESPONDENT-DRIVEN SAMPLING.Sociological methodology · 2016Article
- Brief Report: Respondent-driven Sampling Estimators Under Real and Theoretical Recruitment Conditions of Female Sex Workers in China.Epidemiology (Cambridge, Mass.) · 2015Article
- Challenges to recruiting population representative samples of female sex workers in China using Respondent Driven Sampling.Social science & medicine (1982) · 2015Article
- Siblings, friends, course-mates, club-mates: how adolescent health behavior homophily varies by race, class, gender, and health status.Social science & medicine (1982) · 2015Article
- Network Effects in Blau Space: Imputing Social Context from Survey Data.Socius : sociological research for a dynamic worldArticle
Corrections and comments
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Authors and funding
1 author.
Funding
Abstract
This paper presents a new simulation method to make global network inference from sampled data. The proposed simulation method takes sampled ego network data and uses Exponential Random Graph Models (ERGM) to reconstruct the features of the true, unknown network. After describing the method, the paper presents two validity checks of the approach: the first uses the 20 largest Add Health networks while the second uses the Sociology Coauthorship network in the 1990's. For each test, I take random ego network samples from the known networks and use my method to make global network inference. I find that my method successfully reproduces the properties of the networks, such as distance and main component size. The results also suggest that simpler, baseline models provide considerably worse estimates for most network properties. I end the paper by discussing the bounds/limitations of ego network sampling. I also discuss possible extensions to the proposed approach.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.