nevents: Count number of observed transitions.

In survidm: Inference and Prediction in an Illness-Death Model

Description

Given a dataset of class "survIDM", this function counts the number of observed transitions in the multi-state model.

Usage

nevents(dataidm, state.names=NULL)

Arguments

dataidm	A dataframe including at least four columns named time1, event1, Stime and event, which correspond to disease free survival time, disease free survival indicator, time to death or censoring, and death indicator, respectively.
state.names	Names for the transition states. If NULL (default), transition states are named by "healthy", "illness" and "death".

Details

The colums of the dataset needs to have the format of class "survIDM", which holds the transition matrix of the multi-state model. The arguments time1 and Stime must be numeric and nonnegative; event1 and event must be 0 or 1 if numeric and TRUE or FALSE if logical. Stime must be greater or equal to argument arguments time1. Stime and time1 must be equal when argument event1 equals 0 or FALSE. Argument event must be equal to 0 or FALSE when argument event1 equals 0 or FALSE. When arguments Stime and time1 are equal and argument event1 equals 1 or TRUE, argument event must be equal to 1 or TRUE.

Author(s)

Luis Meira-Machado, Marta Sestelo and Gustavo Soutinho.

References

L. Meira-Machado, J. de Una-Alvarez, C. Cadarso-Suarez, and P. Andersen. Multi-state models for the analysis of time to event data. Statistical Methods in Medical Research, 18:195-222, 2009.

J. de Una-Alvarez and L. Meira-Machado. Nonparametric estimation of transition probabilities in the non-markov illness-death model: A comparative study. Biometrics, 71(2):364-375, 2015.

L. Meira-Machado and M. Sestelo. Estimation in the progressive illness-death model: A nonexhaustive review. Biometrical Journal, 2018.

Examples

nevents(colonIDM)

nevents(colonIDM, c('State0','State1', 'State2'))

survidm documentation built on June 25, 2021, 1:07 a.m.