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Respondent-Driven Sampling×Stratifikovaný výber×
OdborMetodológia dotazníkových prieskumovMetodológia dotazníkových prieskumov
RodinaProcess / pipelineProcess / pipeline
Rok vzniku19971977
TvorcaDouglas HeckathornWilliam G. Cochran
TypProbabilistic chain-referral sampling designProbability-based survey sampling design
Pôvodný zdrojHeckathorn, D. D. (1997). Respondent-driven sampling: A new approach to the study of hidden populations. Social Problems, 44(2), 174–199. DOI ↗Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0-471-16240-7
Ďalšie názvyChain-Referral Sampling, Peer-Referral Sampling, Network-Based Sampling, Katılımcı Güdümlü ÖrneklemeProportional Stratified Sampling, Optimal Allocation Sampling, Stratum-Based Sampling, Tabakalı Örnekleme
Príbuzné32
ZhrnutieRespondent-Driven Sampling (RDS) is a probabilistic chain-referral method designed to reach hidden or hard-to-reach populations that lack a sampling frame. Introduced by sociologist Douglas Heckathorn in 1997, RDS combines snowball recruitment with mathematical weighting based on participants' personal network sizes, allowing researchers to generate population-level estimates even when no complete membership list exists.Stratified sampling is a probability sampling design in which the target population is partitioned into non-overlapping, exhaustive subgroups called strata, and independent probability samples are drawn within each stratum. Formalized by William G. Cochran in Sampling Techniques (1977), the method exploits known population structure to reduce variance and guarantee representativeness of all major subgroups, making it a cornerstone of large-scale survey research and official statistics.
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ScholarGatePorovnať metódy: Respondent-Driven Sampling · Stratified Sampling. Získané 2026-06-15 z https://scholargate.app/sk/compare