Comparar métodos

	Muestreo Bola de Nieve Ponderado	Muestreo Ponderado
Campo	Metodología de encuestas	Metodología de encuestas
Familia	Process / pipeline	Process / pipeline
Año de origen	1997	1940s–1952 (formalized in large-scale government survey work and the Horvitz-Thompson estimator)
Autor original	Douglas D. Heckathorn (formal probability-weighted variant)	Morris H. Hansen, William N. Hurwitz; D. G. Horvitz and D. J. Thompson (theoretical framework)
Tipo	Probability-adjusted chain-referral sampling	Probability sampling design
Fuente seminal	Heckathorn, D. D. (1997). Respondent-driven sampling: A new approach to the study of hidden populations. Social Problems, 44(2), 174–199.	Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407
Alias	weight-adjusted chain-referral sampling, probability-weighted snowball sampling, WSS, weighted referral sampling	probability proportional to size sampling, PPS sampling, unequal probability sampling, importance sampling
Relacionados	5	6
Resumen	Weighted snowball sampling is a chain-referral technique in which participants recruit peers from a hidden or hard-to-reach population, and differential inclusion probabilities are estimated and corrected through statistical weights. Unlike basic snowball sampling, the weighting step allows approximately unbiased population estimates, bridging the gap between convenience-driven recruitment and probability-based inference.	Weighted sampling is a probability-based design in which units are selected with unequal probabilities proportional to a known auxiliary measure of size or importance. Sampling weights — the inverse of inclusion probabilities — are applied during analysis so that each sampled unit correctly represents the population units it stands for. The approach underpins large-scale government, health, and social surveys where simple random sampling would be inefficient.