Description Usage Arguments Details Value Author(s) References See Also Examples

`AT`

can be used to calculate the treatment effect of a binary/continuous/discrete endogenous predictor/treatment, with
corresponding interval obtained using posterior simulation.

1 2 3 4 5 |

`x` |
A fitted |

`nm.end` |
Name of the endogenous variable. |

`eq` |
Number of equation containing the endogenous variable. This is only used for trivariate models. |

`E` |
If |

`treat` |
If |

`type` |
This argument can take three values: |

`ind` |
Binary logical variable. It can be used to calculate the AT for a subset of the data. Note that it does not make sense to
use |

`n.sim` |
Number of simulated coefficient vectors from the posterior distribution of the estimated model parameters. This is used
when |

`prob.lev` |
Overall probability of the left and right tails of the AT distribution used for interval calculations. |

`length.out` |
Ddesired length of the sequence to be used when calculating the effect that a continuous/discrete treatment has on a binary outcome. |

`hd.plot` |
If |

`te.plot` |
For the case of continuous/discrete endogenous variable and binary outcome, if |

`main` |
Title for the plot. |

`xlab` |
Title for the x axis. |

`...` |
Other graphics parameters to pass on to plotting commands. These are used only when |

AT measures the average difference in outcomes under treatment (the binary predictor or treatment assumes value 1) and under control (the binary treatment assumes value 0). Posterior simulation is used to obtain a confidence/credible interval. See the references below for details.

AT can also calculate the effect that a continuous/discrete endogenous variable has on a binary outcome. In this case the effect will depend on the unit increment chosen (as shown by the plot produced).

`res` |
It returns three values: lower confidence interval limit, estimated AT and upper interval limit. |

`prob.lev` |
Probability level used. |

`sim.AT` |
It returns a vector containing simulated values of the average treatment effect. This is used to calculate intervals. |

`Effects` |
For the case of continuous/discrete endogenous variable and binary outcome, it returns a matrix made up of three columns containing the effects for each incremental value in the endogenous variable and respective intervals. |

Maintainer: Giampiero Marra [email protected]

Marra G. and Radice R. (2011), Estimation of a Semiparametric Recursive Bivariate Probit in the Presence of Endogeneity. *Canadian Journal of Statistics*, 39(2), 259-279.

`JRM-package`

, `SemiParBIV`

, `copulaReg`

1 | ```
## see examples for SemiParBIV and copulaReg
``` |

JRM documentation built on July 13, 2017, 5:03 p.m.

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