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The exponentiated power exponential regression model with different regression structures: application in nursing data

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  • F. Prataviera
  • J. C. S. Vasconcelos
  • G. M. Cordeiro
  • E. M. Hashimoto
  • E. M. M. Ortega

Abstract

We define the exponentiated power exponential distribution and propose a regression model with different systematic structures based on the new distribution. We show that the new regression model can be applied to dispersion data since it represents a parametric family of models that includes as sub-models some widely-known regression models. It then can be used more effectively in the analysis of real data. We use maximum likelihood estimation and derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes. Some global-influence measurements are also investigated and simulation studies are performed to evaluate the accuracy of the estimates. We provide an application of the regression model with four systematic structures to nursing activities score data in the Unit of the Medical Clinic of University of São Paulo (USP) Hospital.

Suggested Citation

  • F. Prataviera & J. C. S. Vasconcelos & G. M. Cordeiro & E. M. Hashimoto & E. M. M. Ortega, 2019. "The exponentiated power exponential regression model with different regression structures: application in nursing data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 46(10), pages 1792-1821, July.
    • Handle: RePEc:taf:japsta:v:46:y:2019:i:10:p:1792-1821
    DOI: 10.1080/02664763.2019.1572719
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    Cited by:

    1. Fábio Prataviera & Aline Martineli Batista & Edwin M. M. Ortega & Gauss M. Cordeiro & Bruno Montoani Silva, 2023. "The Logit Exponentiated Power Exponential Regression with Applications," Annals of Data Science, Springer, vol. 10(3), pages 713-735, June.

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