Package: FindIt Version: 1.3.0 Date: 2025-09-20 Title: Finding Heterogeneous Treatment Effects Authors@R: c(person(given = "Naoki", family = "Egami", role = c("aut", "cre"), email = "naoki.egami5@gmail.com"), person(given = "Marc", family = "Ratkovic", role = "aut"), person(given = "Kosuke", family = "Imai", email = "imai@harvard.edu", role = "aut")) Maintainer: Naoki Egami Depends: R (>= 3.1.0), arm Imports: glmnet, lars, Matrix, quadprog, glinternet, igraph, sandwich, lmtest, stats, graphics, utils, limSolve 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. LazyLoad: yes LazyData: yes License: GPL (>= 2) Encoding: UTF-8 RoxygenNote: 7.3.3 NeedsCompilation: no Packaged: 2026-10-10 17:34:01 UTC; root Author: Naoki Egami [aut, cre], Marc Ratkovic [aut], Kosuke Imai [aut] Config/pak/sysreqs: cmake libglpk-dev make libxml2-dev Repository: https://naoki-egami.r-universe.dev Date/Publication: 2025-09-23 22:40:23 UTC RemoteUrl: https://github.com/cran/FindIt RemoteRef: HEAD RemoteSha: 796cf81b580f468aa9cfde34edd41600ef24bca8