plot_gps | R Documentation |

This function estimates the propensity score for each treatment group and then plot the propensity score by each treatment to check covariate overlap.

```
plot_gps(trt, X, cluster.id, method = "Multinomial")
```

`trt` |
A numeric vector representing the treatment groups. |

`X` |
A dataframe or matrix, including all the covariates but not treatments, with rows corresponding to observations and columns to variables. |

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

`method` |
A character indicating how to estimate the propensity score. The default is "Multinomial", which uses multinomial regression to estimate the propensity score. |

A plot

```
library(riAFTBART)
set.seed(20181223)
n = 5 # number of clusters
k = 50 # cluster size
N = n*k # total sample size
cluster.id = rep(1:n, each=k)
tau.error = 0.8
b = stats::rnorm(n, 0, tau.error)
alpha = 2
beta1 = 1
beta2 = -1
sig.error = 0.5
censoring.rate = 0.02
x1 = stats::rnorm(N,0.5,1)
x2 = stats::rnorm(N,1.5,0.5)
trt.train = sample(c(1,2,3), N, prob = c(0.4,0.3,0.2), replace = TRUE)
plot_gps(trt = trt.train, X = cbind(x1, x2), cluster.id = cluster.id)
```

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