demo/FourStateHomogeneous.R

In csetraynor/mctte: Compartmental models applied to time-to-event.

#### Simulation with mctte
library(mrgsolve)
library(tidyverse)
library(mctte)

## Checking model output
mod4 <- mrgsolve::mread_cache("Simulations/simulation_progress4.cpp")

k12 <- 0.04
k14 <- 0.01

k23 <- 0.03
k24 <- 0.02

k34 <- 0.04

mod4   %>% 
  param(q12 = k12,
        q14 = k14,
        
        q23 = k23,
        q24 = k24,
        
        q34 = k34) %>%
  mrgsim(end = 50, delta = 0.1)  %>% plot()

## generate data for practical identifiability
N = 250
### create a dummy covariate dataframe
covs = data.frame(ID = seq_len(N),
                  covs = rep(1, N))

simulate_data <- function(i){
  q12 = k12
  q14 = k14
  
  q23 = k23
  q24 = k24
  
  q34 = k34
  
  qmat = c(0, q12, 0, q14, 0, 0, q23, q24, 0, 0 ,0, q34, 0, 0, 0, 0) 
  
  mod4   %>% 
    param(q12 = k12,
          q14 = k14,
          
          q23 = k23,
          q24 = k24,
          
          q34 = k34) %>%
    mrgsim(end = 50, delta = 0.1) %>%
    as.data.frame() %>%
    mcttesim(., i, covs[i,], nstate = 4, absor = 4, qmat)
}

simdat4 <- seq_len(N) %>% purrr::map( .f = simulate_data) %>% bind_rows()