Comparar métodos

	Muestreo Bola de Nieve Basado en Campo	Muestreo Intencional	Muestreo Basado en el Encuestado
Campo	Metodología de encuestas	Metodología de encuestas	Metodología de encuestas
Familia	Process / pipeline	Process / pipeline	Process / pipeline
Año de origen	1961 (foundational); field variant developed through 1970s–1980s ethnographic and hidden population research	Formalized ~1980–1990	1997
Autor original	Leo A. Goodman (snowball sampling); field adaptation through ethnographic and social network research traditions	Michael Quinn Patton (systematic articulation); roots in early qualitative inquiry	Douglas Heckathorn
Tipo	Non-probability sampling technique	Non-probability sampling strategy	Probabilistic chain-referral sampling design
Fuente seminal	Goodman, L. A. (1961). Snowball sampling. Annals of Mathematical Statistics, 32(1), 148–170.	Patton, M. Q. (1990). Qualitative Evaluation and Research Methods (2nd ed.). Sage. ISBN: 978-0803937796	Heckathorn, D. D. (1997). Respondent-driven sampling: A new approach to the study of hidden populations. Social Problems, 44(2), 174–199.
Alias	in-person snowball sampling, fieldwork chain-referral sampling, field snowball sampling, face-to-face referral sampling	judgmental sampling, selective sampling, criterion-based sampling, purposeful sampling	Chain-Referral Sampling, Peer-Referral Sampling, Network-Based Sampling, Katılımcı Güdümlü Örnekleme
Relacionados	3	4	3
Resumen	Field-based snowball sampling is a non-probability chain-referral technique in which an initial set of in-person contacts (seeds) recruit further participants from within their real-world social networks, expanding the sample iteratively through face-to-face interaction in naturalistic field settings. It is the default snowball approach in ethnographic and community fieldwork, and is particularly valuable when the target population is hidden, hard-to-reach, or lacks a sampling frame.	Purposive sampling is a non-probability strategy in which the researcher deliberately selects participants, documents, or cases that are information-rich with respect to the research question. Rather than drawing units at random, the researcher applies explicit criteria aligned with the study's purpose, maximising the depth and relevance of the data collected. It is the default sampling logic in most qualitative research designs and is also used in mixed-methods and applied evaluative work.	Respondent-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.