rdrbounds | R Documentation |

`rdrbounds`

calculates lower and upper bounds for the
randomization p-value under different degrees of departure from a
local randomized experiment, as suggested by Rosenbaum (2002).

rdrbounds( Y, R, cutoff = 0, wlist, gamma, expgamma, bound = "both", statistic = "ranksum", p = 0, evalat = "cutoff", kernel = "uniform", fuzzy = NULL, nulltau = 0, prob, fmpval = FALSE, reps = 1000, seed = 666 )

`Y` |
a vector containing the values of the outcome variable. |

`R` |
a vector containing the values of the running variable. |

`cutoff` |
the RD cutoff (default is 0). |

`wlist` |
the list of window lengths to be evaluated. By default the program constructs 10 windows around the cutoff, the first one including 10 treated and control observations and adding 5 observations to each group in subsequent windows. |

`gamma` |
the list of values of gamma to be evaluated. |

`expgamma` |
the list of values of exp(gamma) to be evaluated. Default is |

`bound` |
specifies which bounds the command calculates. Options are |

`statistic` |
the statistic to be used in the balance tests. Allowed options are |

`p` |
the order of the polynomial for outcome adjustment model. Default is 0. |

`evalat` |
specifies the point at which the adjusted variable is evaluated. Allowed options are |

`kernel` |
specifies the type of kernel to use as weighting scheme. Allowed kernel types are |

`fuzzy` |
indicates that the RD design is fuzzy. |

`nulltau` |
the value of the treatment effect under the null hypothesis. Default is 0. |

`prob` |
the probabilities of treatment for each unit when assignment mechanism is a Bernoulli trial. This option should be specified as a vector of length equal to the length of the outcome and running variables. |

`fmpval` |
reports the p-value under fixed margins randomization, in addition to the p-value under Bernoulli trials. |

`reps` |
number of replications. Default is 1000. |

`seed` |
the seed to be used for the randomization tests. |

`gamma` |
list of gamma values. |

`expgamma` |
list of exp(gamma) values. |

`wlist` |
window grid. |

`p.values` |
p-values for each window (under gamma = 0). |

`lower.bound` |
list of lower bound p-values for each window and gamma pair. |

`upper.bound` |
list of upper bound p-values for each window and gamma pair. |

Matias Cattaneo, Princeton University. cattaneo@princeton.edu

Rocio Titiunik, Princeton University. titiunik@princeton.edu

Gonzalo Vazquez-Bare, UC Santa Barbara. gvazquez@econ.ucsb.edu

Cattaneo, M.D., R. Titiunik and G. Vazquez-Bare. (2016). Inference in Regression Discontinuity Designs under Local Randomization. *Stata Journal* 16(2): 331-367.

Rosenbaum, P. (2002). Observational Studies. Springer.

# Toy dataset R <- runif(100,-1,1) Y <- 1 + R -.5*R^2 + .3*R^3 + (R>=0) + rnorm(100) # Rosenbaum bounds # Note: low number of replications and windows to speed up process. # The user should increase these values. rdrbounds(Y,R,expgamma=c(1.5,2),wlist=c(.3),reps=100)

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.