Compara mètodes

	Das Gupta Decomposition	Direct Standardization
Camp	Demografia	Demografia
Família	Process / pipeline	Process / pipeline
Any d'origen	1993	2001
Autor original	Prithwis Das Gupta	Classical demographic method (formalized by Preston, Heuveline & Guillot)
Tipus	Multi-factor, multi-population decomposition of a difference between rates	Rate adjustment by reweighting to a standard population
Font seminal	Das Gupta, P. (1993). Standardization and Decomposition of Rates: A User's Manual. U.S. Bureau of the Census, Current Population Reports P23-186.	Preston, S. H., Heuveline, P., & Guillot, M. (2001). Demography: Measuring and Modeling Population Processes. Blackwell. ISBN: 9781557864512
Àlies	Das Gupta's method, Multi-factor rate decomposition, Standardization and decomposition of rates, Das Gupta Ayrıştırması	Directly standardized rate, Age-standardized rate, Direct method of standardization, Doğrudan Standardizasyon
Relacionats	4	4
Resum	Das Gupta decomposition is the general framework for standardizing and decomposing a difference between summary rates when several factors act at once and more than two populations must be compared. Developed by Prithwis Das Gupta and codified in his 1993 U.S. Census Bureau manual, it generalizes Kitagawa's two-population, single-factor decomposition to any number of multiplicatively or additively combined factors and any number of populations, producing factor effects that are exactly additive, symmetric, and internally consistent across every pairwise comparison.	Direct standardization is a demographic technique that makes summary rates comparable across populations by applying each population's group-specific rates — most often age-specific death or disease rates — to a single, common standard population structure. The resulting directly standardized rate answers a counterfactual question: what would the crude rate be if every population had the same age (or other) composition? It removes the confounding effect of differing population structure so that genuine differences in underlying risk can be compared on a level footing.