icmstate (version 0.2.0)

remove_redundant_observations: Remove redundant observations from supplied data frame

Description

Remove redundant observed states from a supplied data frame. Observations are redundant either when we observe an absorbing state multiple times (as we cannot leave an absorbing state), or when a transient state is observed multiple times between transitions (as we cannot have loops, therefore no extra information is provided when we observe a transient state multiple times).

Usage

remove_redundant_observations(gd, tmat)

Value

A data.frame containing the information contained in the input data.frame

gd, but without redundant observations. Depending on whether tmat was specified the function may remove more observations.

Arguments

gd

A data.frame with the following named columns

id:

Subject idenitifier;

state:

State at which the subject is observed at time;

time:

Time at which the subject is observed;

The true transition time between states is then interval censored between the times.

tmat

A transition matrix as created by transMat

Examples

#We simulate some data
#Function to generate evaluation times: at 0 and uniform inter-observation
eval_times <- function(n_obs, stop_time){
 cumsum( c( 0,  runif( n_obs-1, 0, 2*(stop_time-4)/(n_obs-1) ) ) )
}

#Simulate illness-death model data with Weibull transitions
sim_dat <- sim_id_weib(n = 20, n_obs = 6, stop_time = 15, eval_times = eval_times,
                       start_state = "stable", shape = c(0.5, 0.5, 2), 
                       scale = c(5, 10, 10/gamma(1.5)))
visualise_msm(sim_dat)
require(mstate)
sim_dat_clean <- remove_redundant_observations(sim_dat, trans.illdeath())
visualise_msm(sim_dat_clean)