R/bootsfitRISF.R

In JMH: Joint Model of Heterogeneous Repeated Measures and Survival Data

bootsfitRISF <- function(i, N = 200, lambda1 = 0.05,
                         tau = c(0.5, 0.5, -0.2, 0.2, 0.05),
                         CL = 4, CU = 8, 
                         alpha1 = -0.5,
                         vee1 = 2,
                         covbw = matrix(c(0.5, 0.25, 0.25, 0.5), nrow = 2, ncol = 2),
                         seed = 10, maxiter = 1000,
                         increment = 0.25, quadpoint = 15) {
  
  data <- simJMdataRISF(N = N, lambda1 = lambda1, tau = tau,
                        CL = CL, CU = CU, seed = seed + i,
                        increment = increment, alpha1 = alpha1,
                        vee1 = vee1, covbw = covbw)
  ydata <- data$ydata
  cdata <- data$cdata
  
  a <- proc.time()
  fit <- try(JMMLSM(cdata = cdata, ydata = ydata, 
                    long.formula = Y ~ Z1 + Z2 + Z3 + time,
                    surv.formula = Surv(survtime, cmprsk) ~ var1 + var2 + var3,
                    variance.formula = ~ Z1 + Z2 + Z3 + time, maxiter = maxiter, epsilon = 1e-04, 
                    quadpoint = quadpoint, random = ~ 1|ID), silent = FALSE)
  b <- proc.time()
  time <- (b - a)[3]
  
  coef <- vector()
  coefSE <- vector()
  count <- 1
  if ('try-error' %in% class(fit)) {
    coef <- rep(NA, 20)
    coefSE <- rep(NA, 18)
    coef <- list(coef, coefSE)
    names(coef) <- c("coef", "coefSE")
    return(coef)
  } else if (is.null(fit$beta)) {
    coef <- rep(NA, 20)
    coefSE <- rep(NA, 18)
    coef <- list(coef, coefSE)
    names(coef) <- c("coef", "coefSE")
    return(coef)
  } else if (fit$iter == maxiter) {
    coef <- rep(NA, 20)
    coefSE <- rep(NA, 18)
    coef <- list(coef, coefSE)
    names(coef) <- c("coef", "coefSE")
    return(coef)
  } else {
    for (j in 1:length(fit$beta)) {
      coef[count] <- fit$beta[j]
      coefSE[count] <- fit$sebeta[j]
      count <- count + 1
    }
    
    for (j in 1:length(fit$tau)) {
      coef[count] <- fit$tau[j]
      coefSE[count] <- fit$setau[j]
      count <- count + 1
    }
    
    for (j in 1:length(fit$gamma1)) {
      coef[count] <- fit$gamma1[j]
      coefSE[count] <- fit$segamma1[j]
      count <- count + 1
    }
    
    for (j in 1:length(fit$alpha1)) {
      coef[count] <- fit$alpha1[j]
      coefSE[count] <- fit$sealpha1[j]
      count <- count + 1
    }
    
    for (j in 1:length(fit$vee1)) {
      coef[count] <- fit$vee1[j]
      coefSE[count] <- fit$sevee1[j]
      count <- count + 1
    }
    
    for (j in 1:nrow(fit$Sig)) {
      coef[count] <- fit$Sig[j, j]
      coefSE[count] <- fit$seSig[j, j]
      count <- count + 1
    }
    
    coef[count] <- fit$Sig[1, 2]
    coefSE[count] <- fit$seSig[1, 2]
    count <- count + 1
    coef[count] <- time
    count <- count + 1
    coef[count] <- fit$iter
    
    coef <- list(coef, coefSE)
    names(coef) <- c("coef", "coefSE")
    
    return(coef)
  }
  
  
  
  
}