Package: PSor
Type: Package
Title: Semiparametric Principal Stratification Analysis Beyond
        Monotonicity
Version: 0.1.0
Authors@R: c(
    person("Jiaqi", "Tong", email = "jiaqi.tong@yale.edu", role = c("aut", "cre"), comment = c(ORCID = "0009-0005-8922-3386")),
    person("Brennan", "Kahan", role = "ctb"),
    person("Michael O.", "Harhay", role = "ctb"),
    person("Fan", "Li", role = "ctb")
  )
Description: Estimates principal causal effects under principal stratification
    using a margin-free, conditional odds ratio sensitivity parameter. This
    framework unifies the monotonicity assumption and the counterfactual
    intermediate independence assumption, allowing for robust analysis when
    monotonicity may not hold. Computes point estimates, standard errors, and
    confidence intervals for conditionally doubly robust and debiased machine
    learning estimators. The methodological details are described in Tong,
    Kahan, Harhay, and Li (2025) <doi:10.48550/arXiv.2501.17514>.
License: MIT + file LICENSE
URL: https://github.com/deckardt98/PSor
BugReports: https://github.com/deckardt98/PSor/issues
Encoding: UTF-8
Language: en-US
RoxygenNote: 7.3.3
Imports: stats, SuperLearner, caret, dplyr, geex, magrittr, numDeriv
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
NeedsCompilation: no
Packaged: 2026-04-22 21:38:37 UTC; deckard
Author: Jiaqi Tong [aut, cre] (ORCID: <https://orcid.org/0009-0005-8922-3386>),
  Brennan Kahan [ctb],
  Michael O. Harhay [ctb],
  Fan Li [ctb]
Maintainer: Jiaqi Tong <jiaqi.tong@yale.edu>
Repository: CRAN
Date/Publication: 2026-04-24 20:20:21 UTC
