Competing risks survival data under middle censoring—An application to COVID-19 pandemic
نویسندگان
چکیده
Survival data is being analysed here under the middle censoring scheme, using specifically quantile function modelling competing risks. The use of scheme has been shown to be very appropriate COVID-19 pandemic scenario. Cause-specific inference employed. Such inferences are obtained through cumulative incidence based on cause-specific proportional hazards model. baseline lifetime assumed follow a general parametric model namely Weibull distribution, and independent mechanism. We obtain estimates unknown parameters cause specific functions classical as well Bayesian set-up. A Monte Carlo simulation study assesses relative performance different estimators. Finally, real life analysis given for illustration proposed methods. • modelled censored survival data. Middle have nice application in current scenario COVID 19 pandemic. Regression developed via assumption. Maximum likelihood methods estimation used. Bayes squared error LINEX loss functions.
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ژورنال
عنوان ژورنال: Healthcare analytics
سال: 2021
ISSN: ['2772-4425']
DOI: https://doi.org/10.1016/j.health.2021.100006