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- W2317384512 abstract "When the data are the result of a follow-up study and individual survival times are available, statistical models based on counting processes provide a natural framework to estimate the hazard function. For this type of data, the literature extends from purely non parametric to strictly parametric methods and suggests how to adjust for censored and truncated observations. These methods, however, do not cover the area of those biodemographic survival data that are constructed by drawing samples from a cohort at discretely spaced times and are hence gathered in the form of proportions or absolute counts. Examples include life-table data (counts of deaths occurred in an observation period within samples of contemporary survivors) and environmental sampling (counts of survivors in samples drawn from the environment where the individuals live). When using grouped data to estimate the mortality hazard rate, models based either on the Binomial or the Poisson distribution may be useful. Hazard estimation may then be implemented by parametric or nonparametric methods. When a parametric approach is pursued, the hazard function is usually assumed to be known up to a number of parameters to be estimated and plugged into the likelihood function of a Generalized Linear or Nonlinear model (GLM or GNLM), depending on the functional form of both the hazard and the link function. Obviously, the parametric approach is useful when a mathematical theory of aging is available and needs to be tested on empirical data. But even when such a theory is not available, removing sampling errors is still important to capture systematic mortality patterns and nonparametric procedures can be helpful. The principal idea of the present work is that a nonparametric estimate of the mortality hazard function can be derived from a smoothed estimate of the (link-transformed) regression function. In the case of life-table data, for example, the regression function models the expected number of deaths in the sample and the hazard function can be easily" @default.
- W2317384512 created "2016-06-24" @default.
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- W2317384512 date "2004-01-01" @default.
- W2317384512 modified "2023-09-23" @default.
- W2317384512 title "Local Likelihood Methods to Smooth Hazard Rates from Grouped Data" @default.
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