Estimates heterogeneous effects in factorial (and conjoint) models. The methodology employs a Bayesian finite mixture of regularized logistic regressions, where moderators can affect each observation's probability of group membership and a sparsity-inducing prior fuses together levels of each factor while respecting ANOVA-style sum-to-zero constraints. Goplerud, Imai, and Pashley (2024) <doi:10.48550/ARXIV.2201.01357> provide further details.
Version: 1.0.0 Depends: R (≥ 3.4.0) Imports: Rcpp (≥ 1.0.1), Matrix, ggplot2, ParamHelpers, mlr, mlrMBO, smoof, lbfgs, methods, utils, stats LinkingTo: Rcpp, RcppEigen (≥ 0.3.3.4.0) Suggests: FNN, RSpectra, mclust, ranger, tgp, testthat, covr, tictoc Published: 2025-01-13 DOI: 10.32614/CRAN.package.FactorHet Author: Max Goplerud [aut, cre], Nicole E. Pashley [aut], Kosuke Imai [aut] Maintainer: Max Goplerud <mgoplerud at austin.utexas.edu> BugReports: https://github.com/mgoplerud/FactorHet/issues License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] URL: https://github.com/mgoplerud/FactorHet NeedsCompilation: yes Materials: README CRAN checks: FactorHet resultsRetroSearch is an open source project built by @garambo | Open a GitHub Issue
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