Comparar métodos
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| Age-Period-Cohort Model× | Análise de Tábua de Vida× | |
|---|---|---|
| Área | Demografia | Demografia |
| Família≠ | Regression model | Survival analysis |
| Ano de origem≠ | 1983 | 1984 |
| Autor original≠ | Theodore R. Holford (modern estimable-function formulation) | Demographic/actuarial tradition; Chiang |
| Tipo≠ | Regression decomposition of rates into age, period and cohort effects | Age-structured mortality estimator |
| Fonte seminal≠ | Holford, T. R. (1983). The estimation of age, period and cohort effects for vital rates. Biometrics, 39(2), 311–324. DOI ↗ | Chiang, C. L. (1984). The Life Table and Its Applications. Robert E. Krieger Publishing. ISBN: 978-0-89874-565-2 |
| Outros nomes≠ | APC Model, Age-Period-Cohort Analysis, Holford APC Model | Mortality Table, Actuarial Table, Survival Table, Yaşam Tablosu |
| Relacionados≠ | 4 | 3 |
| Resumo≠ | 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. | A life table is a systematic, age-structured summary of the mortality experience of a population. It traces a hypothetical cohort of births — conventionally 100,000 — through successive age intervals, recording how many survive, how many die, and how many person-years are lived at each interval. The method was formalized in its modern probabilistic form by Chiang (1984), synthesizing centuries of actuarial and demographic practice into a rigorous statistical framework applicable to human and biological populations alike. |
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