riskfunc: Computation of hazard ratio and risk ratio estimates based on...

In mexhaz: Mixed Effect Excess Hazard Models

Computation of hazard ratio and risk ratio estimates based on a mexhaz model

Description

Function for computing hazard ratio and risk ratio (ratio of cumulative probabilities of failure) estimates from a model fitted with the mexhaz function. Corresponding confidence intervals are based on the Delta Method or Monte Carlo simulation (based on the assumption of multivariate normality of the model parameter estimates). This function allows the computation of estimates at one time point for several vectors of covariates or for one vector of covariates at several time points. When the model includes a random effect, two types of predictions can be made: (i) marginal predictions (obtained by integration over the random effect distribution) or (ii) conditional predictions either for a particular cluster (using the corresponding shrinkage estimate) or for the value 0 of the random effect.

Usage

riskfunc(object, time.pts, data, data.0, clust.name = NULL, 
marginal = TRUE, type = c("hr", "rr"), conf.int = c("delta",
"simul"), level = 0.95, nb.sim = 10000, seed = NULL)

Arguments

object	an object of class mexhaz, corresponding to a hazard-based regression 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	a data.frame containing the values of the covariates of the population for which hazard ratios or risk ratios are to be calculated.
data.0	a data.frame containing the values of the covariates of the reference population. Each row of data.0 is used as the reference for the corresponding row of data.
clust.name	name of the variable in data (and data.0) containing information on cluster membership to be used to obtain conditional predictions from a mixed effect model. Standard errors of prediction are obtained with the approximation of the conditional mean squared error of prediction (without the second-order bias correction term) described in Booth and Hobert. This argument is not used if the model is a fixed effect model. The default value is NULL: this corresponds to marginal predictions (if marginal is set to TRUE, the preferred option), or to conditional predictions for the value 0 of the random effect (if marginal is set to FALSE).
marginal	logical value controlling the type of predictions returned by the function when the model includes a random intercept. When TRUE, marginal predictions are computed. The marginal survival is obtained by integrating the predicted survival over the distribution of the random effect. When FALSE (default value), conditional predictions depending on the value of the cluster argument are calculated.
type	argument specifying the type of predictions to be calculated. Selection can be made between "hr" (hazard ratio) and "rr" (risk ratio, i.e., ratio of cumulative failure probabilities).
conf.int	method to be used to compute confidence limits. Selection can be made between the following options: "delta" for the Delta Method (default value); "simul" for Monte Carlo simulations (can be time-consuming, especially for models using B-splines for the logarithm of the baseline hazard).
level	a number in (0,1) specifying the level of confidence for computing the confidence intervals of the hazard and the survival. By default, this argument is set to 0.95.
nb.sim	integer value representing the number of simulations used to estimate the confidence limits for the (excess) hazard and the (net) survival. This argument is used only if conf.int is set to "simul".
seed	argument allowing the user to set a random seed for simulations (only relevant when conf.int is set to "simul"). The default value is set to NULL in which case a random seed is automatically generated inside the function.

Value

An object of class resMexhaz that can be used by the function plot.resMexhaz to produce graphics of the hazard ratio or risk ratio curve. It contains the following elements:

results	a data.frame consisting of: the time points at which values have been calculated; the hazard ratio / risk ratio values with their confidence limits.
type	type of results returned by the function. The value is used by plot.resMexhaz and lines.resMexhaz, and can take the values "hr" (hazard ratio) or "rr" (risk ratio).
multiobs	value used by plot.resMexhaz and lines.resMexhaz, and set to FALSE when estimates are computed at several time points for one vector of covariates.
ci.method	method used to compute confidence limits.
level	level of confidence used to compute confidence limits.

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;35:3066-3084 (doi: 10.1002/sim.6881)

Booth JG, Hobert JP. Standard errors of prediction in generalized linear mixed models. J Am Stat Assoc 1998;93:262-272 (doi: 10.2307/2669622).

See Also

plot.resMexhaz, lines.resMexhaz

Examples

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)

## Risk ratio along time for agecr=0.2 compared to agecr=0.1

RR_Modbs1_2 <- riskfunc(Mod_bs1_2, time.pts=seq(0,10,le=101),
data=data.frame(agecr=0.2,depindex=0,IsexH=1),
data.0=data.frame(agecr=0.1,depindex=0,IsexH=1),type="rr",
conf.int="delta")

plot(RR_Modbs1_2)

mexhaz documentation built on Oct. 31, 2022, 5:08 p.m.