Comparar métodos

	Muestreo bola de nieve	Muestreo de Variación Máxima	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	1985 (Lincoln & Guba); elaborated 1990–2002 (Patton)	1997
Autor original	Leo A. Goodman	Lincoln & Guba; systematised by Michael Quinn Patton	Douglas Heckathorn
Tipo	Non-probability sampling technique	Purposive qualitative 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. (2002). Qualitative Research and Evaluation Methods (3rd ed.). Sage. Chapter 5: Purposeful Sampling. ISBN: 978-0761919711	Heckathorn, D. D. (1997). Respondent-driven sampling: A new approach to the study of hidden populations. Social Problems, 44(2), 174–199.
Alias	chain-referral sampling, network sampling, respondent-driven sampling, referral sampling	maximum variation sampling, maximum diversity sampling, MVS, heterogeneous sampling	Chain-Referral Sampling, Peer-Referral Sampling, Network-Based Sampling, Katılımcı Güdümlü Örnekleme
Relacionados	3	5	3
Resumen	Snowball sampling is a non-probability recruitment technique in which initial participants (seeds) refer the researcher to others who meet the study criteria, and those referrals in turn refer further participants. The sample grows incrementally — like a rolling snowball — until the required size or theoretical saturation is reached. It is the method of choice when a target population has no accessible sampling frame, such as undocumented migrants, illicit drug users, survivors of stigmatised experiences, or members of closed professional networks.	Maximum variation sampling is a purposive qualitative sampling strategy in which the researcher deliberately selects cases that span the widest possible range of variation on dimensions central to the study. The goal is not statistical representation but the identification of common patterns that cut across diverse cases as well as the documentation of the unique ways each context shapes the phenomenon under investigation.	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.