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Amostragem Proporcional por Conglomerados×Amostragem em Múltiplos Estágios×
ÁreaMetodologia de surveyMetodologia de survey
FamíliaProcess / pipelineProcess / pipeline
Ano de origem1950s–1960s1950s–1960s (formalized in Kish 1965 and Cochran 1977)
Autor originalFormalized by William G. Cochran and Leslie KishLeslie Kish; William G. Cochran
TipoProbability sampling designProbability sampling design
Fonte seminalCochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407Kish, L. (1965). Survey Sampling. John Wiley & Sons. ISBN: 978-0471109495
Outros nomesPPS cluster sampling, proportional-to-size cluster sampling, size-proportional cluster sampling, probability proportional to size samplingmultistage cluster sampling, multi-stage sampling, nested sampling, hierarchical sampling
Relacionados65
ResumoProportional cluster sampling selects naturally occurring groups (clusters) from a population with probability proportional to each cluster's size, so that larger clusters have a higher chance of selection while every individual element retains an equal overall inclusion probability. This design efficiently handles large, geographically dispersed populations and is the backbone of national health, education, and social surveys worldwide.Multistage sampling is a probability-based design that selects a sample by working through two or more successive levels of a population hierarchy — for example, first selecting regions, then districts within those regions, then households within those districts. It makes large-scale surveys practical when a complete population list is unavailable or when the population is geographically dispersed, by concentrating fieldwork within a manageable number of sampled units at each stage.
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ScholarGateComparar métodos: Proportional Cluster Sampling · Multistage Sampling. Recuperado em 2026-06-17 de https://scholargate.app/pt/compare