var_select | R Documentation |

Performs variable selection with ri-AFTBART using the three thresholding methods introduced in Bleich et al. (2013).

```
var_select(
M.burnin,
M.keep,
M.thin = 1,
status,
y.train,
x.train,
trt.train,
x.test,
trt.test,
cluster.id,
verbose = FALSE,
n_permuate,
alpha = 0.1,
seed = NULL
)
```

`M.burnin` |
A numeric value indicating the number of MCMC iterations to be treated as burn in. |

`M.keep` |
A numeric value indicating the number of MCMC posterior draws after burn in. |

`M.thin` |
A numeric value indicating the thinning parameter. |

`status` |
A vector of event indicators: status = 1 indicates that the event was observed while status = 0 indicates the observation was right-censored. |

`y.train` |
A vector of follow-up times. |

`x.train` |
A dataframe or matrix, including all the covariates but not treatments for training data, with rows corresponding to observations and columns to variables. |

`trt.train` |
A numeric vector representing the treatment groups for the training data. |

`x.test` |
A dataframe or matrix, including all the covariates but not treatments for testing data, with rows corresponding to observations and columns to variables. |

`trt.test` |
A numeric vector representing the treatment groups for the testing data. |

`cluster.id` |
A vector of integers representing the clustering id. The cluster id should be an integer and start from 1. |

`verbose` |
A logical indicating whether to show the progress bar. The default is FALSE. |

`n_permuate` |
Number of permutations of the event time together with the censoring indicator to generate the null permutation distribution. |

`alpha` |
Cut-off level for the thresholds. |

`seed` |
An optional integer value to set the random seed for reproducibility. Default is NULL. |

A list with the following elements:

`var_local_selected:` |
A character vector including all the variables selected using Local procedure. |

`var_max_selected:` |
A character vector including all the variables selected using Global Max procedure. |

`var_global_se_selected:` |
A character vector including all the variables selected using Global SE procedure. |

`vip_perm:` |
The permutation distribution for the variable inclusion proportions generated by permuting the event time together with the censoring indicator. |

`vip_obs:` |
The variable inclusion proportions for the actual data. |

```
set.seed(20181223)
n = 2
k = 50
N = n*k
cluster.id = rep(1:n, each=k)
tau.error = 0.8
b = rnorm(n, 0, tau.error)
alpha = 2
beta1 = 1
beta2 = -1
beta3 = -2
sig.error = 0.5
censoring.rate = 0.02
x1 = rnorm(N,0.5,1)
x2 = rnorm(N,1.5,0.5)
error = rnorm(N,0,sig.error)
logtime = alpha + beta1*x1 + beta2*x2 + b[cluster.id] + error
y = exp(logtime)
C = rexp(N, rate=censoring.rate)
Y = pmin(y,C)
status = as.numeric(y<=C)
trt.train = sample(c(1,2,3), N, prob = c(0.4,0.3,0.2), replace = TRUE)
trt.test = sample(c(1,2,3), N, prob = c(0.3,0.4,0.2), replace = TRUE)
res <- var_select(M.burnin = 10, M.keep = 10, M.thin = 1, status = status,
y.train = Y, trt.train = trt.train, trt.test = trt.test,
x.train = cbind(x1,x2),
x.test = cbind(x1,x2),
cluster.id = cluster.id,
n_permuate = 4,alpha = 0.1,seed = 20181223)
```

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