Comparar métodos

	Amostragem Bola de Neve	Amostragem Intencional	Amostragem por Indicação de Participantes
Área	Metodologia de survey	Metodologia de survey	Metodologia de survey
Família	Process / pipeline	Process / pipeline	Process / pipeline
Ano de origem	1961	Formalized ~1980–1990	1997
Autor original	Leo A. Goodman	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
Fonte 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.
Outros nomes	chain-referral sampling, network sampling, respondent-driven sampling, 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
Resumo	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.	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.