Comparar métodos

	Muestreo Adaptativo de Bola de Nieve	Muestreo Intencional
Campo	Metodología de encuestas	Metodología de encuestas
Familia	Process / pipeline	Process / pipeline
Año de origen	1990s–2000s (as combined approach)	Formalized ~1980–1990
Autor original	Combines principles from S. K. Thompson (adaptive sampling, 1990) and L. A. Goodman (snowball sampling, 1961)	Michael Quinn Patton (systematic articulation); roots in early qualitative inquiry
Tipo	Non-probability / adaptive sampling design	Non-probability sampling strategy
Fuente seminal	Thompson, S. K. (1990). Adaptive cluster sampling. Journal of the American Statistical Association, 85(412), 1050–1059.	Patton, M. Q. (1990). Qualitative Evaluation and Research Methods (2nd ed.). Sage. ISBN: 978-0803937796
Alias	adaptive referral sampling, adaptive chain-referral sampling, dynamic snowball sampling	judgmental sampling, selective sampling, criterion-based sampling, purposeful sampling
Relacionados	4	4
Resumen	Adaptive snowball sampling is a hybrid sampling strategy that recruits initial participants (seeds) from a target population and then dynamically adjusts referral chains based on pre-specified criteria — such as population density, diversity, or theoretical saturation. Combining the chain-referral logic of snowball sampling with the responsive decision rules of adaptive sampling, it is particularly suited to studying rare, hidden, or hard-to-reach populations where conventional frames are unavailable.	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.