dingjshi/ALMOND: Bayesian Analysis of Local Average Treatment Effect (LATE) for Missing or/and Nonnormal Data (ALMOND)

Using Bayesian robust two-stage causal models with instrumental variables to estimate the Local Average Treatment Effect and simultaneously handle the nonnormal and missing data.

Getting started

Package details

AuthorDingjing Shi [aut, cre], Xin Tong [ctb], M. Joseph Meyer [ctb]
MaintainerDingjing Shi <ds4ue@virginia.edu>
LicenseGPL (>= 3.0)
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
dingjshi/ALMOND documentation built on June 18, 2020, 4:32 p.m.