IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v10y2022i19p3644-d934071.html
   My bibliography  Save this article

An Extended Weibull Regression for Censored Data: Application for COVID-19 in Campinas, Brazil

Author

Listed:
  • Gabriela M. Rodrigues

    (Department of Exact Sciences, University of São Paulo, Piracicaba 13418-900, Brazil
    These authors contributed equally to this work.)

  • Edwin M. M. Ortega

    (Department of Exact Sciences, University of São Paulo, Piracicaba 13418-900, Brazil
    These authors contributed equally to this work.)

  • Gauss M. Cordeiro

    (Department of Statistics, Federal University of Pernambuco, Recife 50670-901, Brazil
    These authors contributed equally to this work.)

  • Roberto Vila

    (Department of Statistics, University of Brasilia, Brasilia 70910-900, Brazil
    These authors contributed equally to this work.)

Abstract

This work aims to study the factors that increase the risk of death of hospitalized patients diagnosed with COVID-19 through the odd log-logistic regression model for censored data with two systematic components, as well as provide new mathematical properties of this distribution. To achieve this, a dataset of individuals residing in the city of Campinas (Brazil) was used and simulations were performed to investigate the accuracy of the maximum likelihood estimators in the proposed regression model. The provided properties, such as stochastic representation, identifiability, and moments, among others, can help future research since they provide important information about the distribution structure. The simulation results revealed the consistency of the estimates for different censoring percentages and show that the empirical distribution of the modified deviance residuals converge to the standard normal distribution. The proposed model proved to be efficient in identifying the determinant variables for the survival of the individuals in this study, which can help to find more opportune treatments and medical interventions. Therefore, the new model can be considered an interesting alternative for future works that evaluate censored lifetimes.

Suggested Citation

  • Gabriela M. Rodrigues & Edwin M. M. Ortega & Gauss M. Cordeiro & Roberto Vila, 2022. "An Extended Weibull Regression for Censored Data: Application for COVID-19 in Campinas, Brazil," Mathematics, MDPI, vol. 10(19), pages 1-17, October.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:19:p:3644-:d:934071
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/10/19/3644/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/10/19/3644/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gerine Nijman & Maike Wientjes & Jordache Ramjith & Nico Janssen & Jacobien Hoogerwerf & Evertine Abbink & Marc Blaauw & Ton Dofferhoff & Marjan van Apeldoorn & Karin Veerman & Quirijn de Mast & Jaap , 2021. "Risk factors for in-hospital mortality in laboratory-confirmed COVID-19 patients in the Netherlands: A competing risk survival analysis," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-14, March.
    2. Luis Sánchez & Víctor Leiva & Helton Saulo & Carolina Marchant & José M. Sarabia, 2021. "A New Quantile Regression Model and Its Diagnostic Analytics for a Weibull Distributed Response with Applications," Mathematics, MDPI, vol. 9(21), pages 1-21, November.
    3. Sarah R. Al-Dawsari & Khalaf S. Sultan, 2021. "Inverted Weibull Regression Models and Their Applications," Stats, MDPI, vol. 4(2), pages 1-22, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Adam Braima S. Mastor & Abdulaziz S. Alghamdi & Oscar Ngesa & Joseph Mung’atu & Christophe Chesneau & Ahmed Z. Afify, 2023. "The Extended Exponential-Weibull Accelerated Failure Time Model with Application to Sudan COVID-19 Data," Mathematics, MDPI, vol. 11(2), pages 1-26, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mohammad Anamul Haque & Giuliana Cortese, 2023. "Cumulative Incidence Functions for Competing Risks Survival Data from Subjects with COVID-19," Mathematics, MDPI, vol. 11(17), pages 1-16, September.
    2. Helton Saulo & Roberto Vila & Giovanna V. Borges & Marcelo Bourguignon & Víctor Leiva & Carolina Marchant, 2023. "Modeling Income Data via New Parametric Quantile Regressions: Formulation, Computational Statistics, and Application," Mathematics, MDPI, vol. 11(2), pages 1-25, January.
    3. Josmar Mazucheli & Bruna Alves & Mustafa Ç. Korkmaz & Víctor Leiva, 2022. "Vasicek Quantile and Mean Regression Models for Bounded Data: New Formulation, Mathematical Derivations, and Numerical Applications," Mathematics, MDPI, vol. 10(9), pages 1-23, April.
    4. Alena Vagaská, 2023. "Mathematical–Statistical Nonlinear Model of Zincing Process and Strategy for Determining the Optimal Process Conditions," Mathematics, MDPI, vol. 11(3), pages 1-21, February.
    5. Helton Saulo & Roberto Vila & Giovanna V. Borges & Marcelo Bourguignon, 2022. "Parametric quantile regression for income data," Papers 2207.06558, arXiv.org.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:10:y:2022:i:19:p:3644-:d:934071. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.