AI Article Synopsis
- The article presents an advanced negative binomial cure rate model that uses a piecewise exponential distribution to accommodate both increasing and decreasing hazard functions, unlike standard models that assume a fixed shape.
- This new modeling technique allows for greater flexibility in analyzing cure rates by varying the time intervals considered.
- The authors conduct Monte Carlo simulations and apply their model to real health data from melanoma and leukemia cases to demonstrate its effectiveness.
Article Abstract
In this article, we discuss an extension of the classical negative binomial cure rate model with piecewise exponential distribution of the time to event for concurrent causes, which enables the modeling of monotonic and non-monotonic hazard functions (ie, the shape of the hazard function is not assumed as in traditional parametric models). This approach produces a flexible cure rate model, depending on the choice of time partition. We discuss local influence on this negative binomial power piecewise exponential model. We report on Monte Carlo simulation studies and application of the model to real melanoma and leukemia datasets.
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| http://dx.doi.org/10.1002/sim.9208 | DOI Listing |
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