On bootstrap testing inference in cure rate models

Loose, Laís Helen; Valença, Dione Maria; Bayer, Fábio M.

doi:10.1080/00949655.2018.1522316

Cited by 4 publications

(1 citation statement)

References 36 publications

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“…where in a regression context associated with the incidence model, f p (y i ; λ) and S p (y i ; λ) are obtained in (2) by replacing θ by θ i = q(x ⊤ i ; β). The use of marginal likelihood in cure rate models is common (see for example Tsodikov, 1998;Cancho et al, 2011;Mizoi et al, 2007;Rodrigues et al, 2009;Ortega et al, 2009;Fonseca et al, 2013;Loose et al, 2018). In addition to the marginal likelihood being considered an ordinary likelihood (Cox, 1975), an additional attraction for using this approach is that (7) appears to be a generalization of the usual (log) likelihood considered in survival models with the presence of censoring.…”

Section: Inferencementioning

confidence: 99%

Log-symmetric models with cure fraction with application to leprosy reactions data

B.¹,

Medeiros²,

Valença³

2021

Preprint

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In this paper, we propose a log-symmetric survival model with cure fraction, considering that the distributions of lifetimes for susceptible individuals belong to the log-symmetric class of distributions. This class has continuous, strictly positive, and asymmetric distributions, including the log-normal, log-t-Student, Birnbaum-Saunders, log-logistic I, log-logistic II, log-normalcontaminated, log-exponential-power, and log-slash distributions. The log-symmetric class is quite flexible and allows for including bimodal distributions and outliers. This includes explanatory variables through the parameter associated with the cure fraction. We evaluate the performance of the proposed model through extensive simulation studies and consider a real data application to evaluate the effect of factors on the immunity to leprosy reactions in patients with Hansen's disease.

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