Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Kaplana-Meiera izdzīvošanas novērtētājs× | Lī-Kārtera modelis× | |
|---|---|---|
| Nozare≠ | Dzīvildze | Demogrāfija |
| Saime≠ | Survival analysis | Regression model |
| Izcelsmes gads≠ | 1958 | 1992 |
| Autors≠ | Kaplan, E. L. & Meier, P. | Ronald Lee & Lawrence Carter |
| Tips≠ | Non-parametric survival estimator | Stochastic mortality forecasting model |
| Pirmavots≠ | Kaplan, E. L. & Meier, P. (1958). Nonparametric Estimation from Incomplete Observations. Journal of the American Statistical Association, 53(282), 457–481. DOI ↗ | Lee, R. D., & Carter, L. R. (1992). Modeling and forecasting U.S. mortality. Journal of the American Statistical Association, 87(419), 659–671. DOI ↗ |
| Citi nosaukumi≠ | product-limit estimator, km curve, kaplan-meier sağkalım analizi | LC Model, Lee-Carter Mortality Model, Singular Value Decomposition Mortality Model, Lee-Carter Ölümlülük Modeli |
| Saistītās | 2 | 2 |
| Kopsavilkums≠ | The Kaplan-Meier estimator, introduced by Kaplan and Meier in 1958, is a non-parametric method that estimates the survival curve — the probability of remaining event-free over time — from right-censored time-to-event data. The log-rank test is the companion procedure used to compare survival curves between groups. | The Lee-Carter model is a stochastic framework for modeling and forecasting age-specific mortality rates, introduced by Ronald Lee and Lawrence Carter in their landmark 1992 paper. It decomposes the logarithm of age-specific death rates into an age pattern of mortality, a time-varying index of mortality level, and an age-specific sensitivity of that index, then forecasts the time index using ARIMA time-series methods to generate probabilistic mortality projections. |
| ScholarGateDatu kopa ↗ |
|
|