additive.tvcure: Extract additive term estimates from a tvcure object.

In tvcure: Additive Cure Survival Model with Time-Varying Covariates

Extract additive term estimates from a tvcure object.

Description

Extract additive term estimates from a tvcure object.

Usage

additive.tvcure(obj.tvcure, ngrid = 300, ci.level = 0.95)

Arguments

obj.tvcure	a tvcure.object.
ngrid	number of gridpoints where the fitted additive terms are evaluated.
ci.level	confidence level for the pointwise credible intervals of the additive terms.

Value

A list with following elements:

• f0 : a function estimate of f_0.

• F0 : a function estimate of F_0.

• T : the follow-up time after which a unit is considered ‘cured’.

• nfixed1 : the number of non-penalized regression parameter in the long-term term (or quantum) submodel.

• J1 : number of additive terms in the long-term term (or quantum) submodel.

• additive.lab1 : labels of the additive terms in the long-term term (or quantum) submodel.

• K1 : number of P-spline parameters per additive term in the long-term term (or quantum) submodel.

• knots1 : list of length J1 containing the knots of the additive term in the long-term term (or quantum) submodel.

• f1.grid : list of length J1 containing for each additive term in the long-term term (or quantum) submodel, a list of length 3 with elements <x>, <y.mat> and <y.mat2>

  • Element <x> is a vector of ngrid equidistant values covering the range of values for the covariate ;

  • <y.mat> is (ngrid x 3) matrix containing in column 1 the estimated values of the additive term at <x> and the bounds of the pointwise credible interval for it in the other 2 columns.

  • <y.mat2> is (ngrid x 3) matrix containing in column 1 the estimated values of the additive term at <x> and the bounds of the simultaneous credible region for it in the other 2 columns.

• f1 : list of length J1 containing the estimated function of the corresponding additive term in the long-term term (or quantum) submodel.

• f1.se : list of length J1 containing the estimated standard error function of the corresponding additive term in the long-term term (or quantum) submodel.

The same definitions applies for nfixed2, J2, additive.lab2, K2, knots2, f2.grid, f2, f2.se with the additive terms in the short-term (or timing) submodel.

Author(s)

Philippe Lambert [e-mail]

References

Lambert, P. and Kreyenfeld, M. (2025). Time-varying exogenous covariates with frequently changing values in double additive cure survival model: an application to fertility. Journal of the Royal Statistical Society, Series A. <doi:10.1093/jrsssa/qnaf035>

Examples

require(tvcure)
## Simulated data generation
beta = c(beta0=.4, beta1=-.2, beta2=.15) ; gam = c(gam1=.2, gam2=.2)
data = simulateTVcureData(n=500, seed=123, beta=beta, gam=gam,
                          RC.dist="exponential",mu.cens=550)$rawdata
## TVcure model fitting
tau.0 = 2.7 ; lambda1.0 = c(40,15) ; lambda2.0 = c(25,70) ## Optional
model = tvcure(~z1+z2+s(x1)+s(x2), ~z3+z4+s(x3)+s(x4), data=data,
               tau.0=tau.0, lambda1.0=lambda1.0, lambda2.0=lambda2.0)

## Extract additive term estimates from tvcure object
obj = additive.tvcure(model)
names(obj)

tvcure documentation built on April 12, 2025, 1:58 a.m.