Description Usage Arguments Details Value Author(s) References Examples
The markov assumption may be tested including the sojourn time in the initial state, "times1", and other covariates in the Cox model.
1  markov.test(formula, s, nm.method = "LM", data)

formula 
A 
s 
The first time for obtaining a graphical test of markovianity by comparison of the estimates for transition probabilities. 
nm.method 
The nonmarkov method used to compute the transition probabilities. Defaults to 
data 
A data.frame including at least four columns named

The markov assumption may be tested including the sojourn time in the initial state, "times1", and other covariates in the Cox model. A graphical test for Markovianity is also available.
cox.markov.test 
An object of class 
TPestimates 
Dataframe with estimates of the transition probabilities for AalenJohansen estimator (markovian) and for nonmarkov estimator. Confidence intervals for the transition probability from State 1 to State 2 are also available. 
nm.method 
The nonmarkov method used to compute the transition probabilities. 
s 
The first time for obtaining a graphical test of markovianity by comparison of the estimates for transition probabilities. 
call 
A call object. 
Luis MeiraMachado, Marta Sestelo and Gustavo Soutinho.
L. MeiraMachado, J. de UnaAlvarez, C. CadarsoSuarez, and P. Andersen. Multistate models for the analysis of time to event data. Statistical Methods in Medical Research, 18:195222, 2009.
J. de UnaAlvarez and L. MeiraMachado. Nonparametric estimation of transition probabilities in the nonmarkov illnessdeath model: A comparative study. Biometrics, 71(2):364375, 2015.
L. MeiraMachado and M. Sestelo. Estimation in the progressive illnessdeath model: A nonexhaustive review. Biometrical Journal, 2018.
1 2 3 4 5 6  mk < markov.test(survIDM(time1, event1, Stime, event) ~ 1, s = 365*4,
nm.method = "LM", data = colonIDM)
mk$cox.markov.test
mk$TPestimates
mk$nm.method
plot(mk)

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