Vertaile menetelmiä

	Age-Period-Cohort Model	Direct Standardization
Tieteenala	Väestötiede	Väestötiede
Menetelmäperhe	Regression model	Process / pipeline
Syntyvuosi	1983	2001
Kehittäjä	Theodore R. Holford (modern estimable-function formulation)	Classical demographic method (formalized by Preston, Heuveline & Guillot)
Tyyppi	Regression decomposition of rates into age, period and cohort effects	Rate adjustment by reweighting to a standard population
Alkuperäislähde	Holford, T. R. (1983). The estimation of age, period and cohort effects for vital rates. Biometrics, 39(2), 311–324.	Preston, S. H., Heuveline, P., & Guillot, M. (2001). Demography: Measuring and Modeling Population Processes. Blackwell. ISBN: 9781557864512
Rinnakkaisnimet	APC Model, Age-Period-Cohort Analysis, Holford APC Model	Directly standardized rate, Age-standardized rate, Direct method of standardization, Doğrudan Standardizasyon
Liittyvät	4	4
Tiivistelmä	The age-period-cohort (APC) model decomposes variation in a vital rate — mortality, incidence, fertility — into three temporal dimensions: the age of individuals, the calendar period of observation, and the birth cohort to which they belong. It is the standard framework for asking whether a trend reflects how risk changes with age, contemporaneous period influences affecting all ages at once, or generational effects carried by successive cohorts. Its defining technical challenge is that cohort equals period minus age, an exact linear dependence that makes the three sets of linear effects unidentifiable without further assumptions; Holford's 1983 formulation clarified exactly which quantities can and cannot be estimated.	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.