lcmm (version 1.7.5)

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=2000,Yvalues,...)
"predictlink"(x,ndraws=2000,Yvalues,...)
"predictlink"(x,ndraws=2000,Yvalues,...)

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)

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

See Also

lcmm, multlcmm, plot.lcmm, plot.predictlink

Examples

 ## Not run: 
# 
# ## 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)
# ## End(Not run)