Censoring in rjags - Invalid parent values












1














I'm having troubles reimplementing a model from winbugs on rjags. I'm getting the Invalid parent values error which is the error you get when censoring was not correctly setup, but I can't see my mistake.



This is the original model on WinBugs:



model {
for(i in 1 : N) {
times[i] ~ dweib(v, lambda[i]) T(censor[i],)
lambda[i] <- exp(beta0 + beta1*type[i])
S[i] <- exp(-lambda[i]*pow(times[i],v));
f[i] <- lambda[i]*v*pow(times[i],v-1)*S[i]
h[i] <- f[i]/S[i]
}
beta0 ~ dnorm(0.0, 0.0001)
beta1 ~ dnorm(0.0, 0.0001)
v ~ dexp(0.001)

median0 <- pow(log(2) * exp(-beta0), 1/v)
median1 <- pow(log(2) * exp(-beta0-beta1), 1/v)
}


Setting up a reproducible example:



type <- as.factor(c(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0))
censor <- c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,882,892,1031,
1033,1306,1335,0,1452,1472,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,381,0,0,0,0,0,0,0,0,0,529,0,
0,0,0,0,0,0,0,0,945,0,0,1180,0,0,1277,1397,1512,1519)
times <-c (17,42,44,48,60,72,74,95,103,108,122,144,167,170,183,185,193,195,197,208,234,235,254,307,315,401,
445,464,484,528,542,567,577,580,795,855,NA,NA,NA,NA,NA,NA,1366,NA,NA,1,63,105,129,182,216,250,262,
301,301,342,354,356,358,380,NA,383,383,388,394,408,460,489,499,524,NA,535,562,675,676,748,748,778,
786,797,NA,955,968,NA,1245,1271,NA,NA,NA,NA)
df <- tibble(type = type, censor = censor, time = times) %>%
mutate(censor_limit = replace(censor, censor == 0, max(times, na.rm = TRUE))) %>%
mutate(is_censored = ifelse(is.na(time), 1, 0)) %>%
mutate(time_init = ifelse(is_censored == 1, censor_limit + 1, NA))
df$censor <- NULL
head(df)


And this is the rjags part:



m <- textConnection("model {
for(i in 1 : N) {
isCensored[i] ~ dinterval(times[i], censorLimit[i])
times[i] ~ dweib(v, lambda[i])
lambda[i] <- exp(beta0 + beta1*type[i])
S[i] <- exp(-lambda[i]*pow(times[i],v));
f[i] <- lambda[i]*v*pow(times[i],v-1)*S[i]
h[i] <- f[i]/S[i]
}
beta0 ~ dnorm(0.0, 0.0001)
beta1 ~ dnorm(0.0, 0.0001)
v ~ dexp(0.001)

# Median survival time
median0 <- pow(log(2) * exp(-beta0), 1/v)
median1 <- pow(log(2) * exp(-beta0-beta1), 1/v)
}")

d <- list(N = nrow(df), times = df$time, type = df$type, isCensored = df$is_censored,
censorLimit = df$censor_limit)
inits1 = function() {
inits = list(v = 1, beta0 = 0, beta1=0, times = df$time_init)
}
mod <- jags.model(m, data = d, inits = inits1, n.chains = 3)
update(mod, 1e3)
mod_sim <- coda.samples(model = mod, variable.names = c("lambda", "median0", "median1"), n.iter = 5e3)
mod_csim <- as.mcmc(do.call(rbind, mod_sim))


Output:



Compiling model graph
Resolving undeclared variables
Allocating nodes
Graph information:
Observed stochastic nodes: 164
Unobserved stochastic nodes: 19
Total graph size: 910

Initializing model
Deleting model

Error in jags.model(m, data = d, inits = inits1, n.chains = 3): Error in node h[35]
Invalid parent values









share|improve this question





























    1














    I'm having troubles reimplementing a model from winbugs on rjags. I'm getting the Invalid parent values error which is the error you get when censoring was not correctly setup, but I can't see my mistake.



    This is the original model on WinBugs:



    model {
    for(i in 1 : N) {
    times[i] ~ dweib(v, lambda[i]) T(censor[i],)
    lambda[i] <- exp(beta0 + beta1*type[i])
    S[i] <- exp(-lambda[i]*pow(times[i],v));
    f[i] <- lambda[i]*v*pow(times[i],v-1)*S[i]
    h[i] <- f[i]/S[i]
    }
    beta0 ~ dnorm(0.0, 0.0001)
    beta1 ~ dnorm(0.0, 0.0001)
    v ~ dexp(0.001)

    median0 <- pow(log(2) * exp(-beta0), 1/v)
    median1 <- pow(log(2) * exp(-beta0-beta1), 1/v)
    }


    Setting up a reproducible example:



    type <- as.factor(c(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,
    0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0))
    censor <- c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,882,892,1031,
    1033,1306,1335,0,1452,1472,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,381,0,0,0,0,0,0,0,0,0,529,0,
    0,0,0,0,0,0,0,0,945,0,0,1180,0,0,1277,1397,1512,1519)
    times <-c (17,42,44,48,60,72,74,95,103,108,122,144,167,170,183,185,193,195,197,208,234,235,254,307,315,401,
    445,464,484,528,542,567,577,580,795,855,NA,NA,NA,NA,NA,NA,1366,NA,NA,1,63,105,129,182,216,250,262,
    301,301,342,354,356,358,380,NA,383,383,388,394,408,460,489,499,524,NA,535,562,675,676,748,748,778,
    786,797,NA,955,968,NA,1245,1271,NA,NA,NA,NA)
    df <- tibble(type = type, censor = censor, time = times) %>%
    mutate(censor_limit = replace(censor, censor == 0, max(times, na.rm = TRUE))) %>%
    mutate(is_censored = ifelse(is.na(time), 1, 0)) %>%
    mutate(time_init = ifelse(is_censored == 1, censor_limit + 1, NA))
    df$censor <- NULL
    head(df)


    And this is the rjags part:



    m <- textConnection("model {
    for(i in 1 : N) {
    isCensored[i] ~ dinterval(times[i], censorLimit[i])
    times[i] ~ dweib(v, lambda[i])
    lambda[i] <- exp(beta0 + beta1*type[i])
    S[i] <- exp(-lambda[i]*pow(times[i],v));
    f[i] <- lambda[i]*v*pow(times[i],v-1)*S[i]
    h[i] <- f[i]/S[i]
    }
    beta0 ~ dnorm(0.0, 0.0001)
    beta1 ~ dnorm(0.0, 0.0001)
    v ~ dexp(0.001)

    # Median survival time
    median0 <- pow(log(2) * exp(-beta0), 1/v)
    median1 <- pow(log(2) * exp(-beta0-beta1), 1/v)
    }")

    d <- list(N = nrow(df), times = df$time, type = df$type, isCensored = df$is_censored,
    censorLimit = df$censor_limit)
    inits1 = function() {
    inits = list(v = 1, beta0 = 0, beta1=0, times = df$time_init)
    }
    mod <- jags.model(m, data = d, inits = inits1, n.chains = 3)
    update(mod, 1e3)
    mod_sim <- coda.samples(model = mod, variable.names = c("lambda", "median0", "median1"), n.iter = 5e3)
    mod_csim <- as.mcmc(do.call(rbind, mod_sim))


    Output:



    Compiling model graph
    Resolving undeclared variables
    Allocating nodes
    Graph information:
    Observed stochastic nodes: 164
    Unobserved stochastic nodes: 19
    Total graph size: 910

    Initializing model
    Deleting model

    Error in jags.model(m, data = d, inits = inits1, n.chains = 3): Error in node h[35]
    Invalid parent values









    share|improve this question



























      1












      1








      1







      I'm having troubles reimplementing a model from winbugs on rjags. I'm getting the Invalid parent values error which is the error you get when censoring was not correctly setup, but I can't see my mistake.



      This is the original model on WinBugs:



      model {
      for(i in 1 : N) {
      times[i] ~ dweib(v, lambda[i]) T(censor[i],)
      lambda[i] <- exp(beta0 + beta1*type[i])
      S[i] <- exp(-lambda[i]*pow(times[i],v));
      f[i] <- lambda[i]*v*pow(times[i],v-1)*S[i]
      h[i] <- f[i]/S[i]
      }
      beta0 ~ dnorm(0.0, 0.0001)
      beta1 ~ dnorm(0.0, 0.0001)
      v ~ dexp(0.001)

      median0 <- pow(log(2) * exp(-beta0), 1/v)
      median1 <- pow(log(2) * exp(-beta0-beta1), 1/v)
      }


      Setting up a reproducible example:



      type <- as.factor(c(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,
      0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0))
      censor <- c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,882,892,1031,
      1033,1306,1335,0,1452,1472,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,381,0,0,0,0,0,0,0,0,0,529,0,
      0,0,0,0,0,0,0,0,945,0,0,1180,0,0,1277,1397,1512,1519)
      times <-c (17,42,44,48,60,72,74,95,103,108,122,144,167,170,183,185,193,195,197,208,234,235,254,307,315,401,
      445,464,484,528,542,567,577,580,795,855,NA,NA,NA,NA,NA,NA,1366,NA,NA,1,63,105,129,182,216,250,262,
      301,301,342,354,356,358,380,NA,383,383,388,394,408,460,489,499,524,NA,535,562,675,676,748,748,778,
      786,797,NA,955,968,NA,1245,1271,NA,NA,NA,NA)
      df <- tibble(type = type, censor = censor, time = times) %>%
      mutate(censor_limit = replace(censor, censor == 0, max(times, na.rm = TRUE))) %>%
      mutate(is_censored = ifelse(is.na(time), 1, 0)) %>%
      mutate(time_init = ifelse(is_censored == 1, censor_limit + 1, NA))
      df$censor <- NULL
      head(df)


      And this is the rjags part:



      m <- textConnection("model {
      for(i in 1 : N) {
      isCensored[i] ~ dinterval(times[i], censorLimit[i])
      times[i] ~ dweib(v, lambda[i])
      lambda[i] <- exp(beta0 + beta1*type[i])
      S[i] <- exp(-lambda[i]*pow(times[i],v));
      f[i] <- lambda[i]*v*pow(times[i],v-1)*S[i]
      h[i] <- f[i]/S[i]
      }
      beta0 ~ dnorm(0.0, 0.0001)
      beta1 ~ dnorm(0.0, 0.0001)
      v ~ dexp(0.001)

      # Median survival time
      median0 <- pow(log(2) * exp(-beta0), 1/v)
      median1 <- pow(log(2) * exp(-beta0-beta1), 1/v)
      }")

      d <- list(N = nrow(df), times = df$time, type = df$type, isCensored = df$is_censored,
      censorLimit = df$censor_limit)
      inits1 = function() {
      inits = list(v = 1, beta0 = 0, beta1=0, times = df$time_init)
      }
      mod <- jags.model(m, data = d, inits = inits1, n.chains = 3)
      update(mod, 1e3)
      mod_sim <- coda.samples(model = mod, variable.names = c("lambda", "median0", "median1"), n.iter = 5e3)
      mod_csim <- as.mcmc(do.call(rbind, mod_sim))


      Output:



      Compiling model graph
      Resolving undeclared variables
      Allocating nodes
      Graph information:
      Observed stochastic nodes: 164
      Unobserved stochastic nodes: 19
      Total graph size: 910

      Initializing model
      Deleting model

      Error in jags.model(m, data = d, inits = inits1, n.chains = 3): Error in node h[35]
      Invalid parent values









      share|improve this question















      I'm having troubles reimplementing a model from winbugs on rjags. I'm getting the Invalid parent values error which is the error you get when censoring was not correctly setup, but I can't see my mistake.



      This is the original model on WinBugs:



      model {
      for(i in 1 : N) {
      times[i] ~ dweib(v, lambda[i]) T(censor[i],)
      lambda[i] <- exp(beta0 + beta1*type[i])
      S[i] <- exp(-lambda[i]*pow(times[i],v));
      f[i] <- lambda[i]*v*pow(times[i],v-1)*S[i]
      h[i] <- f[i]/S[i]
      }
      beta0 ~ dnorm(0.0, 0.0001)
      beta1 ~ dnorm(0.0, 0.0001)
      v ~ dexp(0.001)

      median0 <- pow(log(2) * exp(-beta0), 1/v)
      median1 <- pow(log(2) * exp(-beta0-beta1), 1/v)
      }


      Setting up a reproducible example:



      type <- as.factor(c(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,
      0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0))
      censor <- c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,882,892,1031,
      1033,1306,1335,0,1452,1472,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,381,0,0,0,0,0,0,0,0,0,529,0,
      0,0,0,0,0,0,0,0,945,0,0,1180,0,0,1277,1397,1512,1519)
      times <-c (17,42,44,48,60,72,74,95,103,108,122,144,167,170,183,185,193,195,197,208,234,235,254,307,315,401,
      445,464,484,528,542,567,577,580,795,855,NA,NA,NA,NA,NA,NA,1366,NA,NA,1,63,105,129,182,216,250,262,
      301,301,342,354,356,358,380,NA,383,383,388,394,408,460,489,499,524,NA,535,562,675,676,748,748,778,
      786,797,NA,955,968,NA,1245,1271,NA,NA,NA,NA)
      df <- tibble(type = type, censor = censor, time = times) %>%
      mutate(censor_limit = replace(censor, censor == 0, max(times, na.rm = TRUE))) %>%
      mutate(is_censored = ifelse(is.na(time), 1, 0)) %>%
      mutate(time_init = ifelse(is_censored == 1, censor_limit + 1, NA))
      df$censor <- NULL
      head(df)


      And this is the rjags part:



      m <- textConnection("model {
      for(i in 1 : N) {
      isCensored[i] ~ dinterval(times[i], censorLimit[i])
      times[i] ~ dweib(v, lambda[i])
      lambda[i] <- exp(beta0 + beta1*type[i])
      S[i] <- exp(-lambda[i]*pow(times[i],v));
      f[i] <- lambda[i]*v*pow(times[i],v-1)*S[i]
      h[i] <- f[i]/S[i]
      }
      beta0 ~ dnorm(0.0, 0.0001)
      beta1 ~ dnorm(0.0, 0.0001)
      v ~ dexp(0.001)

      # Median survival time
      median0 <- pow(log(2) * exp(-beta0), 1/v)
      median1 <- pow(log(2) * exp(-beta0-beta1), 1/v)
      }")

      d <- list(N = nrow(df), times = df$time, type = df$type, isCensored = df$is_censored,
      censorLimit = df$censor_limit)
      inits1 = function() {
      inits = list(v = 1, beta0 = 0, beta1=0, times = df$time_init)
      }
      mod <- jags.model(m, data = d, inits = inits1, n.chains = 3)
      update(mod, 1e3)
      mod_sim <- coda.samples(model = mod, variable.names = c("lambda", "median0", "median1"), n.iter = 5e3)
      mod_csim <- as.mcmc(do.call(rbind, mod_sim))


      Output:



      Compiling model graph
      Resolving undeclared variables
      Allocating nodes
      Graph information:
      Observed stochastic nodes: 164
      Unobserved stochastic nodes: 19
      Total graph size: 910

      Initializing model
      Deleting model

      Error in jags.model(m, data = d, inits = inits1, n.chains = 3): Error in node h[35]
      Invalid parent values






      r bayesian rjags






      share|improve this question















      share|improve this question













      share|improve this question




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      edited Nov 12 '18 at 22:19







      FranGoitia

















      asked Nov 12 '18 at 21:29









      FranGoitiaFranGoitia

      72121129




      72121129
























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