PHM.test: Cox PH global test for checking the Markov condition on...

In markovMSM: Methods for Checking the Markov Condition in Multi-State Survival Data

Cox PH global test for checking the Markov condition on Multi-state Models.

Description

This function is used to obtain a global test to check the Markov condition for each transition based on Cox Proportional hazard models.

Usage

PHM.test(data, from, to)

Arguments

data	A data frame in long format containing the subject id; from corresponding to the starting state;the receiving state, to; the transition number, trans; the starting time of the transition given by Tstart; the stopping time of the transition, Tstop, and status for the status variable, with 1 indicating an event (transition), 0 a censoring.
from	The starting state of the transition to check the Markov condition.
to	The last state of the considered transition to check the Markov condition.

Value

An object with a list with the following outcomes:

p.value	p-value of Cox global tests for each transition.
from	The starting state of the transition to check the Markov condition.
to	The last state of the considered transition to check the Markov condition.

Author(s)

Gustavo Soutinho and Luis Meira-Machado.

References

Kay, R (1986). A Markov model for analyzing cancer markers and disease states in survival studies. Biometrics 42, 457-481. Soutinho G, Meira-Machado L (2021). Methods for checking the Markov condition in multi-state survival data. Computational Statistics.

Examples

library(markovMSM)
data("colonMSM")
db_wide<-colonMSM
positions<-list(c(2, 3), c(3), c())
namesStates =  c("Alive", "Rec",  "Death")
tmat <-transMatMSM(positions, namesStates)
timesNames = c(NA, "time1","Stime")
status=c(NA, "event1","event")
trans = tmat
db_long<- prepMSM(data=db_wide, trans, timesNames, status)
res1<-PHM.test(data=db_long, from = 2, to=3)
res1

data("ebmt4")
db_wide <- ebmt4
positions=list(c(2, 3, 5, 6), c(4, 5, 6), c(4, 5, 6),
               c(5, 6), c(6), c())
namesStates = c("Tx", "Rec", "AE", "Rec+AE", "Rel", "Death")
tmat <-transMatMSM(positions, namesStates)
timesNames = c(NA, "rec", "ae","recae", "rel", "srv")
status=c(NA, "rec.s", "ae.s", "recae.s","rel.s", "srv.s")
trans = tmat
db_long<- prepMSM(data=db_wide, trans, timesNames, status)
db_long$trans<-as.factor(db_long$trans)
res2<-PHM.test(data=db_long, from = 5, to=6)
res2$p.value
res2$from
res2$to

markovMSM documentation built on Feb. 16, 2023, 8:34 p.m.