predictlink: Confidence intervals for the estimated link functions from `lcmm`, `Jointlcmm` and `multlcmm`

Description

This function provides 95% confidence intervals around the estimated transformation given in estimlink attribute of lcmm, Jointlcmm and multlcmm objects. It can also be used to evaluate the link functions at other values than those given in attribute estimlink of lcmm, Jointlcmm or multlcmm object.

Usage

predictlink(x, ndraws, Yvalues, ...)

Value

An object of class predictlink with values :

- pred :

For a lcmm or Jointlcmm object, a data frame containing the values at which the transformation is evaluated, the transformed values and the lower and the upper limits of the confidence intervals (if ndraws>0).

For a multlcmm object, a data frame containing the indicator of the outcome, the values at which the transformations are evaluated,the transformed values and the lower and the upper limits of the confidence intervals (if ndraws>0).

- object : the object from which the link function is predicted

Arguments

x: an object inheriting from classes lcmm, Jointlcmm or multlcmm.
ndraws: the number of draws that should be generated to approximate the posterior distribution of the transformed values. By default, ndraws=2000.
Yvalues: a vector (for a lcmm or Jointlcmm object) or a matrix (for a multlcmm object) containing the values at which to compute the transformation(s). Default to the values in x$estimlink.
...: other parameters (ignored)

Author

Cecile Proust-Lima and Viviane Philipps

Examples

Run this code


 if (FALSE) {

## Univariate mixed model with splines link funciton
m14<-lcmm(Ydep2~Time+I(Time^2),random=~Time,subject='ID',ng=1,
data=data_lcmm,link="5-manual-splines",intnodes=c(10,20,25),
B=c(-0.89255, -0.09715, 0.56335, 0.21967, 0.61937, -7.90261, 0.75149, 
-1.22357, 1.55832, 1.75324, 1.33834, 1.0968))

##Transformed values of several scores and their confidence intervals
transf.m14 <- predictlink(m14,ndraws=2000,Yvalues=c(0,1,7:30))
plot(transf.m14)


## Multivariate mixed model with splines link functions
m1 <- multlcmm(Ydep1+Ydep2~1+Time*X2+contrast(X2),random=~1+Time,
subject="ID",randomY=TRUE,link=c("4-manual-splines","3-manual-splines"),
intnodes=c(8,12,25),data=data_lcmm,
B=c(-1.071, -0.192,  0.106, -0.005, -0.193,  1.012,  0.870,  0.881,
  0.000,  0.000, -7.520,  1.401,  1.607 , 1.908,  1.431,  1.082,
 -7.528,  1.135 , 1.454 , 2.328, 1.052))
##Confidence intervals for the transformed values (given in m1$estimlink)
transf.m1 <- predictlink(m1,ndraws=200)
plot(transf.m1)
}