On the incidence-prevalence relation and length-biased sampling
نویسندگان
چکیده
منابع مشابه
On the Incidence-prevalence Relation and Length-biased Sampling Vittorio Addona, Masoud Asgharian and David B. Wolfson
For many diseases, logistic and other constraints often render large incidence studies difficult, if not impossible, to carry out. This becomes a drawback, particularly when a new incidence study is needed each time the disease incidence rate is investigated in a different population. However, by carrying out a prevalent cohort study with follow-up it is possible to estimate the incidence rate ...
متن کاملSome Asymptotic Results of Kernel Density Estimator in Length-Biased Sampling
In this paper, we prove the strong uniform consistency and asymptotic normality of the kernel density estimator proposed by Jones [12] for length-biased data.The approach is based on the invariance principle for the empirical processes proved by Horváth [10]. All simulations are drawn for different cases to demonstrate both, consistency and asymptotic normality and the method is illustrated by ...
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A Simple Test for Detection of Length-biased Sampling
When the probability of selecting an individual in a population is proportional to its magnitude, it is called length biased sampling. Length-biased sampling (LBS) situations may occur in biological studies, clinical trials, reliability, queuing models, survival analysis and population studies where a proper sampling frame is absent. In such situations items are sampled at rate proportional to ...
متن کاملsome asymptotic results of kernel density estimator in length-biased sampling
in this paper, we prove the strong uniform consistency and asymptotic normality of the kernel density estimator proposed by jones [12] for length-biased data.the approach is based on the invariance principle for the empirical processes proved by horváth [10]. all simulations are drawn for different cases to demonstrate both, consistency and asymptotic normality and the method is illustrated by ...
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ژورنال
عنوان ژورنال: Canadian Journal of Statistics
سال: 2009
ISSN: 0319-5724,1708-945X
DOI: 10.1002/cjs.10011