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Comments on: Nonparametric estimation in mixture cure models with covariates

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A Discussion to this article was published on 01 June 2023

The Original Article was published on 17 May 2023

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References

  • Bremhorst V, Kreyenfeld M, Lambert P (2016) Fertility progression in Germany: an analysis using flexible nonparametric cure survival models. Demogr Res 35:505–534

    Article  Google Scholar 

  • Bremhorst V, Kreyenfeld M, Lambert P (2019) Nonparametric double additive cure survival models: an application to the estimation of the nonlinear effect of age at first parenthood on fertility progression. Stat Model 19:275–279

    Article  MATH  Google Scholar 

  • Bremhorst V, Lambert P (2016) Flexible estimation in cure survival models using Bayesian P-splines. Comput Stat Data Anal 93:270–284

    Article  MathSciNet  MATH  Google Scholar 

  • Gressani O, Lambert P (2018) Fast Bayesian inference using Laplace approximations in a flexible promotion time cure model based on P-splines. Comput Stat Data Anal 124:151–167

    Article  MathSciNet  MATH  Google Scholar 

  • Lambert P, Bremhorst V (2019) Estimation and identification issues in the promotion time cure model when the same covariates influence long- and short-term survival. Biom J 61(2):275–289

    Article  MathSciNet  MATH  Google Scholar 

  • Lambert P, Bremhorst V (2020) Inclusion of time-varying covariates in cure survival models with an application in fertility studies. J R Stat Soc A 183:333–354

    Article  MathSciNet  Google Scholar 

  • Lambert P, Kreyenfeld M (2023) Exogenous time-varying covariates in double additive cure survival model with application to fertility. arXiv:2302.00331

  • López-Cheda A, Peng Y, Jácome M (2023) Nonparametric estimation in mixture cure models with covariates. Test

  • Yakovlev A, Tsodikov A (1996) Stochastic models for tumor of latency and their biostatistical applications. World Scientific Publishing, Singapore

    Book  MATH  Google Scholar 

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Funding

ARC project IMAL (grant 20/25-107) financed by the Wallonia-Brussels Federation and granted by the Academie universitaire Louvain.

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Correspondence to Philippe Lambert.

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Lambert, P. Comments on: Nonparametric estimation in mixture cure models with covariates. TEST 32, 506–509 (2023). https://doi.org/10.1007/s11749-023-00860-3

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