Inference and Prediction in an Illness-Death Model

Documentation for package ‘survidm’ version 1.3.2

survidm-package	survidm: Inference and Prediction in an Illness-Death Model
autoplot	Visualization of objects of class 'survIDM' with ggplot2 graphics.
autoplot.survIDM	Visualization of objects of class 'survIDM' with ggplot2 graphics.
Beran	Estimation of the conditional distribution function of the response, given the covariate under random censoring.
bladderIDM	Bladder Cancer Recurrences.
CIF	Nonparametric estimation of the Cumulative Incident Functions in the illness-death model
colonIDM	Chemotherapy for Stage B/C colon cancer.
coxidm	Fit proportional hazards regression model in each transition of the Illness-Death Model.
KM	Kaplan-Meier product-limit estimate of survival
KMW	Kaplan-Meier weights
LLW	Local linear weights
markov.test	This function is used to test the markov assumption in the illness-death model.
nevents	Count number of observed transitions.
NWW	Nadaraya-Watson weights.
PKM	Presmoothed Kaplan-Meier product-limit estimate of survival
PKMW	Presmoothed Kaplan-Meier weights
plot.survIDM	Plot for an object of class "survIDM".
print.cmm	Summarizing fits of 'cmm' class
print.survIDM	Summarizing fits of 'survIDM' class
sojourn	Nonparametric estimation of the Sojourn time distributions in the recurrence state in the illness-death model
summary.cmm	Summarizing fits of 'cmm' class
summary.survIDM	Summarizing fits of 'survIDM' class
survIDM	Create a survIDM object
survidm	survidm: Inference and Prediction in an Illness-Death Model
tprob	Nonparametric estimation of transition probabilities in the illness-death model