Literature DB >> 24847899

Semiparametric M-quantile regression for count data.

Emanuela Dreassi1, M Giovanna Ranalli2, Nicola Salvati3.   

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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Entities:  

Keywords:  Disease mapping; Negative Binomial; ecological regression; geoadditive models; penalized splines; robust method

Mesh:

Year:  2014        PMID: 24847899     DOI: 10.1177/0962280214536636

Source DB:  PubMed          Journal:  Stat Methods Med Res        ISSN: 0962-2802            Impact factor:   3.021


  1 in total

1.  On the Use of Aggregate Survey Data for Estimating Regional Major Depressive Disorder Prevalence.

Authors:  Domingo Morales; Joscha Krause; Jan Pablo Burgard
Journal:  Psychometrika       Date:  2021-09-06       Impact factor: 2.290

  1 in total

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