predict.idm: Predictions for an illness-death model using either a...

In SmoothHazard: Smooth models for interval-censored data with applications to survival and illness-death models

Description

Predict transition probabilities and cumulative probabilities from an object of class idmSplines with confidence intervals are calculated.

Usage

## S3 method for class 'idm'
predict(object, s, t, Z01, Z02, Z12, nsim = 2000, CI = TRUE,
  ...)

Arguments

object	an idm class objects returned by a call to the idm function
s	time at prediction.
t	time for prediction.
Z01	vector for the values of the covariates on the transition 0 –> 1 (in the same order as the covariates within the call. The default values are all 0.
Z02	vector for the values of the covariates on the transition 0 –> 2 (in the same order as the covariates within the call. The default values are all 0.
Z12	vector for the values of the covariates on the transition 1 –> 2 (in the same order as the covariates within the call. The default values are all 0.
nsim	number of simulations for the confidence intervals calculations. The default is 2000.
CI	boolean: with (TRUE) or without (WRONG) confidence intervals for the predicted values. The default is TRUE.
...	other parameters.

Value

a list containing the following predictions with pointwise confidence intervals:

p00	the transition probability p_{00}.
p01	the transition probability p_{01}.
p11	the transition probability p_{11}.
p12	the transition probability p_{12}.
p02_0	the probability of direct transition from state 0 to state 2.
p02_1	the probability of transition from state 0 to state 2 via state 1.
p02	transition probability p_{02}. Note that p02=p_02_0+p02_1.
F01	the lifetime risk of disease. F01=p01+p02_1.
F0.	the probability of exit from state 0. F0.=p02_0+p01+p02_1.

Author(s)

R: Celia Touraine <[e-mail]> Fortran: Pierre Joly <[e-mail]>

See Also

idm

Examples

## Not run: 
data(Paq1000)
library(prodlim)
fit <- idm(formula02=Hist(time=t,event=death,entry=e)~certif,
formula01=Hist(time=list(l,r),event=dementia)~certif,data=Paq1000)

pred <- predict(fit,s=70,t=80,Z01=c(1),Z02=c(1),Z12=c(1))
pred

fit.splines <-  idm(formula02=Hist(time=t,event=death,entry=e)~certif,
		formula01=Hist(time=list(l,r),event=dementia)~certif,
                formula12=~1,
                method="Splines",
		data=Paq1000)

pred <- predict(fit.splines,s=70,t=80,Z01=c(1),Z02=c(1))
pred


## End(Not run)

SmoothHazard documentation built on May 2, 2019, 4:43 p.m.