Σύγκριση μεθόδων

	Δειγματοληψία Δυσανάλογης Στρωματοποίησης	Δειγματοληψία Πολλαπλών Σταδίων
Πεδίο	Μεθοδολογία Επισκοπήσεων	Μεθοδολογία Επισκοπήσεων
Οικογένεια	Process / pipeline	Process / pipeline
Έτος προέλευσης	1934	1950s–1960s (formalized in Kish 1965 and Cochran 1977)
Δημιουργός	Jerzy Neyman	Leslie Kish; William G. Cochran
Τύπος	Probability sampling design	Probability sampling design
Θεμελιώδης πηγή	Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407	Kish, L. (1965). Survey Sampling. John Wiley & Sons. ISBN: 978-0471109495
Εναλλακτικές ονομασίες	disproportionate stratified sampling, unequal-probability stratified sampling, oversampling stratified design, non-proportional stratified sampling	multistage cluster sampling, multi-stage sampling, nested sampling, hierarchical sampling
Συναφείς	6	5
Σύνοψη	Disproportional stratified sampling divides the population into mutually exclusive strata and deliberately draws different proportions from each stratum — oversampling small or analytically important subgroups and undersampling large ones. Post-hoc weighting restores population-level representativeness when overall estimates are needed. First formalised by Jerzy Neyman in 1934, it is the standard approach when subgroup-level precision matters as much as total-population estimates.	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.