qte: A package for computating quantile treatment effects

Main class of objects. A `QTE`

object is returned by
all of the methods that compute the QTE or QTET.

1 2 3 4 5 6 7 8 9 | ```
QTE(qte, ate = NULL, qte.se = NULL, qte.lower = NULL, qte.upper = NULL,
ate.se = NULL, ate.lower = NULL, ate.upper = NULL, pscore.reg = NULL,
probs, type = "On the Treated", F.treated.t = NULL,
F.untreated.t = NULL, F.treated.t.cf = NULL, F.treated.tmin1 = NULL,
F.treated.tmin2 = NULL, F.treated.change.tmin1 = NULL,
F.untreated.change.t = NULL, F.untreated.change.tmin1 = NULL,
F.untreated.tmin1 = NULL, F.untreated.tmin2 = NULL,
condQ.treated.t = NULL, condQ.treated.t.cf = NULL, eachIterList = NULL,
inffunct = NULL, inffuncu = NULL)
``` |

`qte` |
The Quantile Treatment Effect at each value of probs |

`ate` |
The Average Treatment Effect (or Average Treatment Effect on the Treated) |

`qte.se` |
A vector of standard errors for each qte |

`qte.lower` |
A vector of lower confidence intervals for each qte (it is based on the bootstrap confidence interval – not the se – so it may not be symmyetric about the qte |

`qte.upper` |
A vector of upper confidence intervals for each qte (it is based on the bootstrap confidence interval – not the se – so it may not be symmetric about the qte |

`ate.se` |
The standard error for the ATE |

`ate.lower` |
Lower confidence interval for the ATE (it is based on the bootstrap confidence intervall – not the se – so it may not be symmetric about the ATE |

`ate.upper` |
Upper confidence interval for the ATE (it is based on the bootstrap confidence interval – not the se – so it may not be symmetric about the ATE |

`pscore.reg` |
The results of propensity score regression, if specified |

`probs` |
The values for which the qte is computed |

`type` |
Takes the values "On the Treated" or "Population" to indicate whether the estimated QTE is for the treated group or for the entire population |

`F.treated.t` |
Distribution of treated outcomes for the treated group at period t |

`F.untreated.t` |
Distribution of untreated potential outcomes for the untreated group at period t |

`F.treated.t.cf` |
Counterfactual distribution of untreated potential outcomes for the treated group at period t |

`F.treated.tmin1` |
Distribution of treated outcomes for the treated group at period tmin1 |

`F.treated.tmin2` |
Distribution of treated outcomes for the treated group at period tmin2 |

`F.treated.change.tmin1` |
Distribution of the change in outcomes for the treated group between periods tmin1 and tmin2 |

`F.untreated.change.t` |
Distribution of the change in outcomes for the untreated group between periods t and tmin1 |

`F.untreated.change.tmin1` |
Distribution of the change in outcomes for the untreated group between periods tmin1 and tmin2 |

`F.untreated.tmin1` |
Distribution of outcomes for the untreated group in period tmin1 |

`F.untreated.tmin2` |
Distribution of outcomes for the untreated group in period tmin2 |

`condQ.treated.t` |
Conditional quantiles for the treated group in period t |

`condQ.treated.t.cf` |
Counterfactual conditional quantiles for the treated group in period t |

`eachIterList` |
An optional list of the outcome of each bootstrap iteration |

`inffunct` |
The influence function for the treated group; used for inference when there are multiple periods and in the case with panel data. It is needed for computing covariance terms in the variance-covariance matrix. |

`inffuncu` |
The influence function for the untreated group |

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