Computationally Efficient Estimation for the Generalized Odds Rate Mixture Cure Model With Interval-Censored Data

Zhou, Jie; Zhang, Jiajia

doi:10.1080/10618600.2017.1349665

Cited by 28 publications

(42 citation statements)

References 37 publications

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“…As discussed above, Zhou et al. 13 and Chen et al. 31 proposed Poisson-variable-based EM algorithms for interval-censored data with a cured subgroup.…”

Section: Maximum Likelihood Estimation and Expectation-maximization Algorithmmentioning

confidence: 99%

“…The mixture cure model has been extensively investigated in the literature under right or interval censoring. 13,19–32 In particular, Zhou et al. 13 and Chen et al.…”

Section: Introductionmentioning

confidence: 99%

“…13,19–32 In particular, Zhou et al. 13 and Chen et al. 31 discussed regression analysis of interval-censored data with the generalized odds rate and semiparametric transformation mixture cure models, respectively.…”

Section: Introductionmentioning

confidence: 99%

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A semiparametric mixture model approach for regression analysis of partly interval-censored data with a cured subgroup

Sun

Wang

et al. 2021

Stat Methods Med Res

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Failure time data with a cured subgroup are frequently confronted in various scientific fields and many methods have been proposed for their analysis under right or interval censoring. However, a cure model approach does not seem to exist in the analysis of partly interval-censored data, which consist of both exactly observed and interval-censored observations on the failure time of interest. In this article, we propose a two-component mixture cure model approach for analyzing such type of data. We employ a logistic model to describe the cured probability and a proportional hazards model to model the latent failure time distribution for uncured subjects. We consider maximum likelihood estimation and develop a new expectation-maximization algorithm for its implementation. The asymptotic properties of the resulting estimators are established and the finite sample performance of the proposed method is examined through simulation studies. An application to a set of real data on childhood mortality in Nigeria is provided.

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“…As discussed above, Zhou et al. 13 and Chen et al. 31 proposed Poisson-variable-based EM algorithms for interval-censored data with a cured subgroup.…”

Section: Maximum Likelihood Estimation and Expectation-maximization Algorithmmentioning

confidence: 99%

“…The mixture cure model has been extensively investigated in the literature under right or interval censoring. 13,19–32 In particular, Zhou et al. 13 and Chen et al.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A semiparametric mixture model approach for regression analysis of partly interval-censored data with a cured subgroup

Sun

Wang

et al. 2021

Stat Methods Med Res

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“…Furthermore, the miCoPTCM package (Bertrand et al, 2020) fits semiparametric promotion time cure models with possibly mis-measured covariates, while the mixcure package (Peng, 2020) implements parametric and semiparametric mixture cure models based on existing R packages. For interval-censored data with a cure fraction, the GORcure package (Zhou et al, 2017) implements the generalized odds rate mixture cure model, including the PH mixture cure model and the proportional odds mixture cure model as special cases. The intercure package (Brettas, 2016) provides an implementation of semiparametric cure rate estimators for interval-censored data using bounded cumulative hazard and frailty models.…”

Section: Introductionmentioning

confidence: 99%

npcure: An R Package for Nonparametric Inference in Mixture Cure Models

López-Cheda¹,

Jácome²,

López-de-Ullibarri³

2021

The R Journal

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Mixture cure models have been widely used to analyze survival data with a cure fraction. They assume that a subgroup of the individuals under study will never experience the event (cured subjects). So, the goal is twofold: to study both the cure probability and the failure time of the uncured individuals through a proper survival function (latency). The R package npcure implements a completely nonparametric approach for estimating these functions in mixture cure models, considering right-censored survival times. Nonparametric estimators for the cure probability and the latency as functions of a covariate are provided. Bootstrap bandwidth selectors for the estimators are included. The package also implements a nonparametric covariate significance test for the cure probability, which can be applied with a continuous, discrete, or qualitative covariate.

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“…For comparison purpose, we also fit each simulated sample using the usual PH mixture cure (PHMixCure) model in which only linear covariate effects are included in the incidence and latency parts. Corresponding results obtained by R package GORCure (Zhou et al, 2018) are also presented in both tables. It can be seen that, in the presence of covariates ξ i and V with nonlinear effects in both the incidence and latency parts, misspecifying their effects linearly in the PHMixCure model leads to considerably biased parameter estimates with large SDs and consequently poor performance of CPs.…”

Section: Simulation Studiesmentioning

confidence: 72%

Extended semiparametric mixture cure models for interval censored data

Liu¹

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Analysis of the survival data with a subgroup of cured subjects arising in a clinical trial is commonly performed using a mixture cure model. Existing studies of the two-component mixture cure model assume a logistic regression for the cure probability and a conventional survival model for failure times of susceptible subjects. In this thesis, two extended semiparametric mixture cure models are proposed to analyze interval-censored data in which the failure times are recorded as intervals and there is a subgroup of subjects to be cured. The first proposal is to use the Bayesian doubly semiparametric mixture cure model to incorporate the nonlinear effects of risk factors both in the probability of being cured and the survival risks in the latency stage. The second proposal is based on a generalized accelerated hazards cure model to describe the time-scaled effects in the latency stage.I would like to express my very great appreciation to Professor Xiang Liming, my supervisor, for her support, warmly encouragement, constructive suggestions, and patient guidance for this research work. Her conscientious attitude and hardworking inspire me to explore the unknown fields in future research.

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Computationally Efficient Estimation for the Generalized Odds Rate Mixture Cure Model With Interval-Censored Data

Cited by 28 publications

References 37 publications

A semiparametric mixture model approach for regression analysis of partly interval-censored data with a cured subgroup

A semiparametric mixture model approach for regression analysis of partly interval-censored data with a cured subgroup

npcure: An R Package for Nonparametric Inference in Mixture Cure Models

Extended semiparametric mixture cure models for interval censored data

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