Comparar métodos

	Muestreo Adaptativo de Máxima Variación	Muestreo bola de nieve
Campo	Metodología de encuestas	Metodología de encuestas
Familia	Process / pipeline	Process / pipeline
Año de origen	1990s–2000s (practice codified in qualitative methods literature)	1961
Autor original	Synthesizes Patton (maximum variation) and Thompson (adaptive sampling)	Leo A. Goodman
Tipo	Adaptive purposive qualitative sampling strategy	Non-probability sampling technique
Fuente seminal	Patton, M. Q. (1990). Qualitative Evaluation and Research Methods (2nd ed.). Sage. [Maximum variation sampling, pp. 169–183] ISBN: 978-0803937796	Goodman, L. A. (1961). Snowball sampling. Annals of Mathematical Statistics, 32(1), 148–170.
Alias	adaptive purposive maximum variation sampling, iterative maximum variation sampling, adaptive heterogeneous sampling, AMVS	chain-referral sampling, network sampling, respondent-driven sampling, referral sampling
Relacionados	5	3
Resumen	Adaptive maximum variation sampling is a purposive qualitative sampling strategy that combines the logic of maximum variation sampling — deliberately selecting cases that differ as widely as possible on key dimensions — with an adaptive, iterative recruitment process. Rather than fixing the full sample in advance, the researcher continuously reviews emerging data to identify which types of cases are underrepresented and recruits new participants to fill those gaps, maximizing heterogeneity throughout data collection.	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.