Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Relational Gompertz Fertility Model× | Brass Relational Logit Model× | |
|---|---|---|
| Domeniu | Demografie | Demografie |
| Familie | Regression model | Regression model |
| Anul apariției≠ | 1984 | 1971 |
| Autorul original≠ | William Brass; standard refined by Heather Booth | William Brass |
| Tip≠ | Relational parametric model of the cumulative fertility schedule | Two-parameter relational mortality model |
| Sursa seminală≠ | Booth, H. (1984). Transforming Gompertz's function for fertility analysis: The development of a standard for the relational Gompertz function. Population Studies, 38(3), 495–506. DOI ↗ | Brass, W. (1971). On the scale of mortality. In W. Brass (Ed.), Biological Aspects of Demography. Taylor & Francis / Barnes & Noble. ISBN: 9780850660425 |
| Denumiri alternative≠ | Brass Relational Gompertz Model, Gompertz Relational Fertility Model, Relational Gompertz Function | Brass Logit System, Brass Logit Life-Table Model, Two-Parameter Logit Mortality Model, Brass İlişkisel Logit Modeli |
| Înrudite | 4 | 4 |
| Rezumat≠ | The relational Gompertz model expresses any population's cumulative fertility schedule as a simple linear transformation of a fixed standard schedule, after both are mapped through a double-logarithm (gompit) transform. Developed by William Brass and given its widely used standard by Heather Booth, it characterizes the entire age pattern of fertility with just two parameters — α, which shifts the schedule earlier or later, and β, which controls how concentrated or spread out childbearing is. This makes it a robust tool for smoothing, fitting, and especially for correcting and estimating fertility from the limited and error-prone data common in developing countries. | The Brass relational logit model is a two-parameter system for representing and smoothing a life table by relating it to a chosen standard. Introduced by William Brass in 1971, it transforms the survivorship function with a logit and posits that the logits of any two life tables are linearly related, so that an entire age pattern of mortality can be summarized by just two parameters — a level parameter and a parameter governing the balance of childhood versus adult mortality. |
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