The Use of Network Sampling for Locating the Seriously III
Bibliographic Data
| ID | 9097324 |
|---|---|
| Authors | Seymour Sudman (University of Illinois Urbana-Champaign, corresponding author), Howard E Freeman (University of California, Los Angeles) |
| Year | 1988 |
| Volume | 26 |
| Issue | 10 |
| Pages | 992-999 |
| Publication date | 1988-10-01 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Medical Care (JOURNAL) |
| Journal identifiers | ISSN: 0025-7079 • E-ISSN: 1537-1948 |
| Publisher | Ovid Technologies (Wolters Kluwer Health) (PUBLISHER) |
| DOI | 10.1097/00005650-198810000-00007 |
| PMID | 3172869 |
| OpenAlex | W1989531922 |
| Language | EN |
| Citations received | 7 |
| References cited | 2 |
Network sampling, based on the experience of conducting the large-scale 1986 Robert Wood Johnson Foundation National Access to Health Care Survey, was shown to be a viable alternative to more conventional procedures for oversampling persons with a low incidence and prevalence of health conditions. The network sampling approach was a more economical and methodologically less obtrusive means of increasing sample size of persons with desired characteristics than conventional procedures. The approach requires estimating the incidence, prevalence, or both of the required characteristics in the population. As the proportion of persons in the population with the characteristic increases, network sampling may lose its attractiveness. However, this has to be judged both in economic terms and in terms of the methodologic consequences of using other procedures to increase the size of subgroups of interest. As discussed, additional methodologic work is required on the consequences of network sampling for study group representativeness and sampling bias. However, network sampling, in the authors' opinion, is sufficiently promising to warrant methodologic explorations to answer these and other relevant questions about its use
Environmental health · Oversampling · Population · Representativeness heuristic · Sample (material) · Sample size determination · Sampling (signal processing) · Sampling bias · Sampling design · Sampling frame · Statistics · Survey sampling · Telecommunications · Computer Science · Health disparities and outcomes · HIV, Drug Use, Sexual Risk · Mathematics · Medicine · Mental Health and Patient Involvement
Sampling Rare and Elusive Populations
When the snowball fails to roll and the use of ‘horizontal’ networking in qualitative social research
Generalization and Statistical Inference From Snowball Samples1
Knowledge, acceptability, and attitudes regarding minimally invasive tissue sampling (Mits) techniques in Brazil
Methodological issues of retrospective surveys for measuring mortality of highly clustered diseases
Regular source of ambulatory care and access to health services
Field research in conflict environments
| Unique citing works | 7 |
|---|---|
| Citations per year | 0.18 |
| Citation span | 1988 - 2026 (39) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 7 |