Description Usage Arguments Examples

`Subpop`

conducts set inference on the groups of most and least affected. When `subgroup = NULL`

, output is for whole sample.
Otherwise the results are subgroup. The results can be visualized using the
`Subpopplot`

command. The output of `Subpop`

is a list containing four components: `most`

, `least`

, `u`

and `sub`

.
As the names indicate, `most`

and `least`

denote the confidence sets for the most and least affected units. `u`

stores the u-th most
and least affected index and `sub`

stores the indicators for subpopulations.

1 2 3 4 |

`fm` |
Regression formula |

`data` |
The data in use |

`method` |
Models to be used for estimating partial effects. Four options: |

`var.type` |
The type of parameter in interest. Three options: |

`var.T` |
Variable T in interset. Should be a character. |

`compare` |
If parameter in interest is categorical, then user needs to specify which two category to
compare with. Should be a 1 by 2 character vector. For example, if the two levels to compare
with is 1 and 3, then |

`subgroup` |
Subgroup in interest. Default is |

`samp_weight` |
Sampling weight of data. If null then function implements empirical bootstrap. If data specifies sampling weight, put that in and the function implements weighted (i.i.d exponential weights) bootstrap. |

`taus` |
Indexes for quantile regression. Default is |

`u` |
Percentile of most and least affected. Default is set to be 0.1. |

`alpha` |
Size for confidence interval. Shoule be between 0 and 1. Default is 0.1 |

`B` |
Number of bootstrap draws. Default is set to be 10. For more accurate results, we recommend 500. |

`ncores` |
Number of cores for computation. Default is set to be 1. For large dataset, parallel computing is highly recommended since bootstrap is time-consuming. |

`seed` |
Pseudo-number generation for reproduction. Default is 1. |

`boot.type` |
Type of bootstrap. Default is |

1 2 3 |

yuqimemeda/SortedEffects documentation built on May 23, 2019, 9:51 a.m.

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