Package: PND.heter.cluster
Type: Package
Title: Estimating the Cluster Specific Treatment Effects in Partially
        Nested Designs
Version: 0.1.0
Authors@R: person(given = "Xiao",
                  family = "Liu",
                  role = c("aut", "cre"),
                  email = "xiao.liu@austin.utexas.edu")
Maintainer: Xiao Liu <xiao.liu@austin.utexas.edu>
Description: Implements the methods for assessing heterogeneous cluster-specific treatment effects in partially nested designs as described in Liu (2024) <doi:10.1037/met0000723>. The estimation uses the multiply robust method, allowing for the use of machine learning methods in model estimation (e.g., random forest, neural network, and the super learner ensemble).  Partially nested designs (also known as partially clustered designs) are designs where individuals in the treatment arm are assigned to clusters (e.g., teachers, tutoring groups, therapists), whereas individuals in the control arm have no such clustering. 
Depends: R (>= 4.0.0)
Imports: stats, mvtnorm, SuperLearner, ranger, xgboost, nnet, origami,
        boot, tidyverse, dplyr, purrr, magrittr, glue
Suggests: testthat, knitr, rmarkdown
URL: https://github.com/xliu12/PND.heter
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.1
NeedsCompilation: no
Packaged: 2025-06-03 13:39:44 UTC; xl9663
Author: Xiao Liu [aut, cre]
Repository: CRAN
Date/Publication: 2025-06-05 10:00:08 UTC
Built: R 4.6.0; ; 2026-04-30 21:06:47 UTC; unix
