additive.tvcure {tvcure} | R Documentation |
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 |
|
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 off_0
. -
F0
: a function estimate ofF_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 p.lambert@uliege.be
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)