DESCRIPTION

Package: FindIt
Version: 1.0
Date: 2016-12-22
Title: Finding Heterogeneous Treatment Effects
Author: Naoki Egami <negami@princeton.edu>, Marc Ratkovic <ratkovic@princeton.edu>, Kosuke Imai <kimai@princeton.edu>,
Maintainer: Naoki Egami <negami@princeton.edu>
Depends: R (>= 3.1.0), arm
Imports: glmnet, lars, Matrix, quadprog, ggplot2, stats, graphics,
        utils
Description: The heterogeneous treatment effect estimation procedure 
        proposed by Imai and Ratkovic (2013)<DOI: 10.1214/12-AOAS593>.  
        The proposed method is applicable, for
        example, when selecting a small number of most (or least)
        efficacious treatments from a large number of alternative
        treatments as well as when identifying subsets of the
        population who benefit (or are harmed by) a treatment of
        interest. The method adapts the Support Vector Machine
        classifier by placing separate LASSO constraints over the
        pre-treatment parameters and causal heterogeneity parameters of
        interest. This allows for the qualitative distinction between
        causal and other parameters, thereby making the variable
        selection suitable for the exploration of causal heterogeneity. 
	The package also contains the function, CausalANOVA, which estimates 
	the average marginal interaction effects by a regularized ANOVA as 
	proposed by Egami and Imai (2016+). 
LazyLoad: yes
LazyData: yes
License: GPL (>= 2)