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FindIt  

Finding Heterogeneous Treatment Effects
View on CRAN: Click here


Download and install FindIt package within the R console
Install from CRAN:
install.packages("FindIt")

Install from Github:
library("remotes")
install_github("cran/FindIt")

Install by package version:
library("remotes")
install_version("FindIt", "1.3.0")



Attach the package and use:
library("FindIt")
Maintained by
Naoki Egami
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2012-12-10
Latest Update:
Description:
The heterogeneous treatment effect estimation procedure proposed by Imai and Ratkovic (2013). 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 a class of functions, CausalANOVA, which estimates the average marginal interaction effects (AMIEs) by a regularized ANOVA as proposed by Egami and Imai (2019). It contains a variety of regularization techniques to facilitate analysis of large factorial experiments.
How to cite:
Naoki Egami (2012). FindIt: Finding Heterogeneous Treatment Effects. R package version 1.3.0, https://cran.r-project.org/web/packages/FindIt. Accessed 11 Mar. 2026.
Previous versions and publish date:
0.1 (2012-12-10 17:29), 0.2 (2013-01-25 07:53), 0.3 (2013-02-01 07:53), 0.4 (2015-02-08 00:31), 0.5 (2015-02-27 12:11), 1.0 (2016-12-31 08:42), 1.1.1 (2017-08-24 22:51), 1.1.2 (2017-10-05 23:00), 1.1.3 (2018-01-21 18:28), 1.1.4 (2018-04-11 09:02), 1.1 (2017-08-14 20:33), 1.2.0 (2019-11-20 22:50)
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