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The hydration of cement takes place within the water-filled capillary pores. However, environmental elements can disrupt this process by evaporating water from the concrete surfaces. Sealed concrete with a water-cement ratio below 0.5 experiences self-desiccation, leading to water loss. The water loss in concrete is mitigated by curing. This technique involves keeping the concrete saturated to maintain the necessary temperature and moisture conditions, to optimally fill the spaces in the cement...
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Concrete members with a small surface-to-volume ratio are cured by oiling and moistening the forms before casting the concrete member. These forms can be left in place for a prolonged period to prevent moisture loss, and can be wetted if made of a material suitable for wetting. If the forms are removed early, the concrete member is moistened and covered with polythene sheets to maintain moisture. For large horizontal concrete surfaces exposed to dry weather, a temporary covering is suspended...
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The single-index/Cox mixture cure model.

Maïlis Amico1,2, Ingrid Van Keilegom1,2, Catherine Legrand2

  • 1Research Center for Operations Research and Business Statistics, KU Leuven, Leuven, Belgium.

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|November 16, 2018
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Summary
This summary is machine-generated.

This study introduces a flexible single-index model for cure rate mixture models, improving upon the standard logistic assumption. The new approach enhances survival analysis for cured and non-cured patient subpopulations.

Keywords:
EM algorithmcure modelskernel smoothinglogistic modelproportional hazards modelsurvival analysis

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Area of Science:

  • Biostatistics
  • Survival Analysis
  • Statistical Modeling

Background:

  • Survival analysis often encounters 'cured' patients who never experience the event of interest.
  • Mixture cure models are common for covariate data, assuming distinct cured and non-cured subpopulations.
  • Existing models often use a logistic assumption for mixing probabilities, which can be restrictive.

Purpose of the Study:

  • To propose a flexible single-index model for mixing probabilities in mixture cure models.
  • To address the limitations of the traditional logistic model assumption.
  • To develop an estimation method for this new flexible model.

Main Methods:

  • A single-index model is proposed for the mixing probabilities.
  • A Cox proportional hazards model is assumed for the survival function of non-cured subjects.
  • Maximum likelihood estimation is employed for model parameter estimation.

Main Results:

  • The proposed single-index model offers greater flexibility compared to the logistic model.
  • Simulation studies compare the performance of single-index and logistic models.
  • The new model and estimation method are applied to a real-world breast cancer dataset.

Conclusions:

  • The single-index cure rate mixture model provides a more adaptable alternative to standard models.
  • This approach avoids the curse-of-dimensionality while maintaining flexibility.
  • The method demonstrates practical utility in analyzing complex survival data, such as in cancer research.