Bayesian Inference in Regression Discontinuity Designs

Documentation for package ‘LoTTA’ version 0.1.1

LoTTA_fuzzy_BIN	LoTTA_fuzzy_BIN
LoTTA_fuzzy_CONT	LoTTA_fuzzy_CONT
LoTTA_plot_effect	LoTTA_plot_effect
LoTTA_plot_effect_DIS	Function that visualizes the impact of the cutoff location on the treatment effect estimate. It plots too figures. The bottom figure depicts the posterior density of the cutoff location. The top figure depicts the box plot of the treatment effect given the cutoff point. If the prior on the cutoff location was discrete each box corresponds to a distinct cutoff point. If the prior was continuous each box correspond to an interval of cutoff values (the number of intervals can be changed through nbins).
LoTTA_plot_outcome	LoTTA_plot_outcome
LoTTA_plot_treatment	Function that plots the median (or another quantile) of the LoTTA posterior treatment probability function along with the quanatile-based credible interval. The function is plotted on top of the binned input data. To bin the data, the score data is divided into bins of fixed length, then the proportion of treated is calculated in each bin. The proportions are plotted against the average values of the score in the corresponding bins. The data is binned separately on each side of the cutoff, the cutoff is marked on the plot with a dotted line. In case of an unknown cutoff, the MAP estimate is used.
LoTTA_sharp_BIN	LoTTA_sharp_BIN
LoTTA_sharp_CONT	LoTTA_sharp_CONT
LoTTA_treatment	LoTTA_treatment