R: Inference and Prediction in an Illness-Death Model

# Inference and Prediction in an Illness-Death Model

## Documentation for package ‘survidm’ version 1.3.2

- DESCRIPTION file
- Package README

## Help Pages

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