Function for predicting the (excess) hazard and the corresponding
(net) survival from
a model fitted with the mexhaz function for a particular vector
of covariates. If the survival model
was fitted with an expected hazard, the estimates obtained are excess
hazard and net survival estimates. When the model includes a random
effect, the predicted values are obtained for the value 0 of the
random effect. Confidence limits
can be obtained by Monte-Carlo simulation (for all types of baseline
hazard) and by the Delta Method (not available for Weibull hazard).
This function allows the computation of the hazard and the survival at
one time point for several vectors of covariables or for one vector of
covariables at
several time points.
an object of class mexhaz, corresponding to a
survival model fitted with the mexhaz function.
time.pts
a vector of numerical values representing the time
points at which predictions are requested. Time values greater than
the maximum follow-up time on which the model estimation was based
are discarded.
data.val
a data.frame containing the values of the
covariables at which predictions should be calculated.
conf.int
method to be used to compute confidence
limits. Selection can be made between the following options:
"none" indicates absence of confidence limits estimation
(default value);
"delta" for the Delta Method (this option is not available for
models using a Weibull hazard);
"simul" for Monte Carlo simulations (can be time-consuming, especially for models using B-splines for the logarithm of the baseline hazard).
nb.sim
integer value representing the number of simulations
used to estimate the 95% confidence limits for the (excess) hazard and the (net) survival. This argument is used only if conf.int="simul".
Value
An object of class predMexhaz that can be used by
the functions plot.predMexhaz and points.predMexhaz to produce graphics of the (excess) hazard and
the (net) survival. It contains the following elements:
call
the mexhaz function call on which the model is based.
results
a data.frame consisting of: the time
points at which the (excess) hazard and the (net) survival have been
calculated; the values of the covariables used to estimate the
(excess) hazard and the (net) survival; the
(excess) hazard values with their confidence limits; and the (net) survival values with their confidence limits.
variances
a data.frame consisting of two columns: the
variance of the logarithm of the (excess) hazard and the variance of
the (excess) cumulative hazard for each time points or each
vector of covariables. These variances can be used to estimate the population
(net) survival. The object variances is produced only when
B-splines are used to model the logarithm of the
baseline (excess) hazard with the option conf.int="delta".
type
the type of predictions produced. Can take the value
"multitime" (computation of the hazard and the survival at
at several time points for one vector of covariables) or
multiobs (computation of the hazard and the survival at
at one time point for several vectors of covariables). This value is
used by plot.predMexhaz and points.predMexhaz.
ci.method
the method used to compute confidence limits.
nb.sim
number of simulations used to estimate the 95% confidence
limits (set to NA if confidence limits were not requested or
calculated with the Delta Method).
Author(s)
Hadrien Charvat, Aurelien Belot
References
Charvat H, Remontet L, Bossard N, Roche L, Dejardin O,
Rachet B, Launoy G, Belot A; CENSUR Working Survival Group. A
multilevel excess hazard model to estimate net survival on
hierarchical data allowing for non-linear and non-proportional effects
of covariates. Stat Med 2016. (doi: 10.1002/sim.6881)
data(simdatn1)
## Fit of a fixed-effect hazard model, with the baseline hazard
## described by a linear B-spline with two knots at 1 and 5 year and with
## effects of age (agecr), deprivation index (depindex) and sex (IsexH)
Mod_bs1_2 <- mexhaz(formula=Surv(time=timesurv,
event=vstat)~agecr+depindex+IsexH, data=simdatn1, base="exp.bs",
degree=1, knots=c(1,5), verbose=0)
## Prediction at several time points for one vector of covariates
Pred_Modbs1_2A <- predMexhaz(Mod_bs1_2, time.pts=seq(0.1,10,by=0.1),
data.val=data.frame(agecr=0,depindex=0.5,IsexH=1), conf.int="delta")
## Prediction for several vectors of covariates at one time point
Pred_Modbs1_2B <- predMexhaz(Mod_bs1_2, time.pts=10,
data.val=data.frame(agecr=c(-0.2,-0.1,0), depindex=c(0.5,0.5,0.5),
IsexH=c(1,1,1)), conf.int="delta")
## Prediction for all individuals of the study population at one time point
Pred_Modbs1_2C <- predMexhaz(Mod_bs1_2, time.pts=10,
data.val=simdatn1, conf.int="delta")
providing 
.