# ------------------------------------------------ # CITATION.cff file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # ------------------------------------------------ cff-version: 1.2.0 message: 'To cite package "ctreeMI" in publications use:' type: software license: GPL-3.0-or-later title: 'ctreeMI: Conditional Inference Trees with Stacked Multiple Imputation' version: 0.1.0 abstract: Implements the stacked-imputation workflow for conditional inference trees ('ctree') described in Sherlock et al. (2026) . When data contain missing values, multiply imputed datasets (e.g., from 'mice') are stacked vertically and a single 'ctree' is fit on the combined data. To correct for the artificially inflated sample size introduced by stacking, the pruning significance threshold is divided by the number of imputations M (the Stack/M correction), producing a conservative but interpretable single tree that incorporates imputation uncertainty without requiring pooling of structurally different trees. Also exports stack_imputations() and rescale_alpha() as standalone utilities. The underlying 'ctree' algorithm is provided by 'partykit' (Hothorn & Zeileis, 2015; Hothorn, Hornik & Zeileis, 2006 ). authors: - family-names: Sherlock given-names: Phillip email: phillip.sherlock@ufl.edu orcid: https://orcid.org/0000-0003-0433-3681 repository: https://cran.r-universe.dev repository-code: https://github.com/Phillip-Sherlock/ctreeMI commit: 08c92d62de0821666f4e59573843b05266436384 url: https://github.com/Phillip-Sherlock/ctreeMI date-released: '2026-07-10' contact: - family-names: Sherlock given-names: Phillip email: phillip.sherlock@ufl.edu orcid: https://orcid.org/0000-0003-0433-3681