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The competing risk vignette has an example that shows how we can fit competing risks model by manually stacking data in order to more easily share coefficients. However, the resulting cumulative hazar…
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Implementare i competing risks nei modelli che li supportano
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- Use cmprsk library in python for competing risks
- On backend just uses R package for competing risks
- Then you also have rsf libraries neural nets for this (worth looking into?)
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### Expected Behaviour
Benchmarking to complete for a competing risks model
### Actual Behaviour
`Error in dimnames(x) Loading required package: mlr3
library(mlr3extralearners)
#>
#> Attachi…
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Is there any implementation of Deep Cox Mixtures that supports competing risks?
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- [ ] basic
- [ ] time-varying effects
- [ ] time-dependent covariates (`concurrent`)
- [ ] cumulative effects (`cumulative`)
- [ ] integrate into `sim_pexp` (check if `length(RHS(formula)) > 1`…
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Hi there,
I was wondering if you would like to collaborate in adding functionality that includes uncertain endpoints in the competing risks framework. I'm working on a method paper and would apprec…
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Hi @chjackson,
Do you have any thoughts about whether this package would ever add support for being able to use flexible parametric models to directly model the cause-specific cumulative incidences…