Comparer des méthodes

	Échantillonnage inverse	Échantillonnage double	Échantillonnage par ensembles classés
Domaine	Échantillonnage	Échantillonnage	Échantillonnage
Famille	Process / pipeline	Process / pipeline	Process / pipeline
Année d'origine	1945	1938	1952
Auteur d'origine	John Burdon Sanderson Haldane	Jerzy Neyman	Glenn A. McIntyre
Type	Sequential sampling method	Multi-phase sampling design	Sampling design methodology
Source fondatrice	Haldane, J. B. S. (1945). On a method of estimating frequencies. Biometrika, 33(3), 222–224.	Neyman, J. (1938). Contribution to the theory of sampling human populations. Journal of the American Statistical Association, 33(201), 101–116.	McIntyre, G. A. (1952). A method for unbiased selective sampling using ranked sets. Australian Journal of Agricultural Research, 3(4), 385–390.
Alias	Sequential Sampling	Two-Phase Sampling	RSS
Apparentées	3	4	4
Résumé	Inverse Sampling is a sequential sampling strategy where sampling continues until a fixed number of occurrences of a rare event or item of interest is observed. Introduced by J. B. S. Haldane in 1945, it is particularly efficient for estimating rare event probabilities or proportions when the target is sparse and costly to detect.	Double Sampling (also called two-phase or multistage sampling) is a survey design in which a large preliminary sample is collected using inexpensive methods or partial information, then a smaller subsample is drawn from it and measured in detail. Pioneered by Jerzy Neyman in 1938, it is particularly useful when a cheap surrogate measurement is available but true measurement is expensive.	Ranked Set Sampling (RSS) is a data collection method introduced by G. A. McIntyre in 1952 that improves estimation efficiency when visual ranking of units is easier or cheaper than actual measurement. By deliberately selecting and measuring units that are ranked as most likely to yield desired outcomes, RSS reduces variance compared to simple random sampling while maintaining unbiasedness.