ArticleDemography2022
Using Social Networks to Sample Migrants and Study the Complexity of Contemporary Immigration: An Evaluation Study.
Article in Demography, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed, 6 citations in OpenAlex.
- "It's Whack, It's Not Gonna Work": Feasibility of Sociocentric Network Recruitment for Interventions Among Black, Latine, and Caribbean Priority Populations in New York City.AIDS education and prevention : official publication of the International Society for AIDS Education · 2025Article
- The impact of the COVID-19 pandemic on network dynamics among Chinese immigrants in the United States.International migration (Geneva, Switzerland) · 2025Article
- Studying Chinese immigrants' spatial distribution in the Raleigh-Durham area by linking survey and commercial data using romanized names.Journal of the Royal Statistical Society. Series A, (Statistics in Society) · 2025Article
- The impact of two types of COVID-19-related discrimination and contemporaneous stressors on Chinese immigrants in the US South.SSM. Mental health · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
We test the effectiveness of a link-tracing sampling approach-network sampling with memory (NSM)-to recruit samples of rare immigrant populations with an application among Chinese immigrants in the Raleigh-Durham area of North Carolina. NSM uses the population network revealed by data from the survey to improve the efficiency of link-tracing sampling and has been shown to substantially reduce design effects in simulated sampling. Our goals are to (1) show that it is possible to recruit a probability sample of a locally rare immigrant group using NSM and achieve high response rates; (2) demonstrate the feasibility of the collection and benefits of new forms of network data that transcend kinship networks in existing surveys and can address unresolved questions about the role of social networks in migration decisions, the maintenance of transnationalism, and the process of social incorporation; and (3) test the accuracy of the NSM approach for recruiting immigrant samples by comparison with the American Community Survey. Our results indicate feasibility, high performance, cost-effectiveness, and accuracy of the NSM approach to sample immigrants for studies of local immigrant communities. This approach can also be extended to recruit multisite samples of immigrants at origin and destination.
Indexed as
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.