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Updated: Apr 29, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Semiparametric M-quantile regression for count data
Emanuela Dreassi1, M Giovanna Ranalli2, Nicola Salvati3
1Dipartimento di Statistica, Informatica, Applicazioni, Università di Firenze, Firenze, Italy dreassi@disia.unifi.it.
Abstract:
Lung cancer incidence over 2005-2010 for 326 Local Authority Districts in England is investigated by ecological regression. Motivated from mis-specification of a Negative Binomial additive model, a semiparametric Negative Binomial M-quantile regression model is introduced. The additive part relates to those univariate or bivariate smoothing components, which are included in the model to capture nonlinearities in the predictor or to account for spatial dependence. All such components are estimated using penalized splines. The results show the capability of the semiparametric Negative Binomial M-quantile regression model to handle data with a strong spatial structure.
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Quartile
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