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cff-version: 1.2.0
message: 'To cite package "PND.heter.cluster" in publications use:'
type: software
license: GPL-2.0-only
title: 'PND.heter.cluster: Estimating the Cluster Specific Treatment Effects in Partially
  Nested Designs'
version: 0.1.0
doi: 10.32614/CRAN.package.PND.heter.cluster
abstract: Implements the methods for assessing heterogeneous cluster-specific treatment
  effects in partially nested designs as described in Liu (2024) <https://doi.org/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.
authors:
- family-names: Liu
  given-names: Xiao
  email: xiao.liu@austin.utexas.edu
repository: https://xliu12.r-universe.dev
repository-code: https://github.com/xliu12/PND.heter
commit: 7099a2096dbf6f24a133af82ced0793a1bc981d6
url: https://github.com/xliu12/PND.heter
date-released: '2025-06-03'
contact:
- family-names: Liu
  given-names: Xiao
  email: xiao.liu@austin.utexas.edu