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A survival regression with cure fraction applied to cervical cancer

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Abstract

A new survival model is proposed in the presence of surviving fractions and unobserved dispersion. It is obtained by considering several latent factors (or risks) that generated the observed lifetime which follows a generalized Poisson distribution, and it includes as a special case, the promotion time cure model. We explore maximum likelihood tools for inference issues by aid of the expectation maximization algorithm for estimating the parameters while model discrimination problem is treated by the aid of the likelihood ratio test. The new regression is applied to cervical cancer data to evaluate covariates effects in the cured fraction and non-cured group.

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Acknowledgements

The research of this paper was supported by grant from Brazilian agencies (CAPES and CNPq). CNPq Scholarship—Brazil (166774/2020-0)

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Correspondence to Edwin M. M. Ortega.

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Cancho, V.G., Bedia, E.C., Cordeiro, G.M. et al. A survival regression with cure fraction applied to cervical cancer. Comput Stat 38, 403–418 (2023). https://doi.org/10.1007/s00180-022-01233-4

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  • DOI: https://doi.org/10.1007/s00180-022-01233-4

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