Comparar métodos

	Muestreo de máxima variación multinivel	Muestreo Estratificado
Campo	Metodología de encuestas	Metodología de encuestas
Familia	Process / pipeline	Process / pipeline
Año de origen	1990s–2000s	1977
Autor original	Synthesized from Patton's maximum variation sampling (1990) and multi-level survey design traditions	William G. Cochran
Tipo	Purposive qualitative/mixed-methods sampling design	Probability-based survey sampling design
Fuente seminal	Patton, M. Q. (2002). Qualitative Research and Evaluation Methods (3rd ed.). Sage. [Chapter 5: Maximum variation sampling and purposeful sampling strategies] ISBN: 978-0761919711	Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0-471-16240-7
Alias	hierarchical maximum variation sampling, nested maximum diversity sampling, multi-tier purposive variation sampling, MLMVS	Proportional Stratified Sampling, Optimal Allocation Sampling, Stratum-Based Sampling, Tabakalı Örnekleme
Relacionados	5	2
Resumen	Multi-level maximum variation sampling is a purposive strategy that deliberately selects cases at two or more nested organizational levels — such as schools within districts, or patients within clinics — while maximizing heterogeneity on key dimensions at each level. The aim is to capture the full range of variation within a hierarchically structured population so that patterns common across diverse contexts can be identified and context-specific differences can be documented with credibility.	Stratified sampling is a probability sampling design in which the target population is partitioned into non-overlapping, exhaustive subgroups called strata, and independent probability samples are drawn within each stratum. Formalized by William G. Cochran in Sampling Techniques (1977), the method exploits known population structure to reduce variance and guarantee representativeness of all major subgroups, making it a cornerstone of large-scale survey research and official statistics.