Package: dScoreTest
Title: Debiased Score Tests for Goodness of Fit and Model Comparison
Version: 1.0.0
Authors@R: c(
    person("F. Richard", "Guo", email = "ricguo@umich.edu",
           role = c("aut", "cre", "cph"),
           comment = c(ORCID = "0000-0002-2081-7398")),
    person("Aditya", "Dhawan", email = "ad950@cam.ac.uk",
           role = "aut"))
Description: Debiased (Neyman-orthogonalized) score tests for assessing
    whether a semiparametric or parametric regression model is well-specified
    and for comparing nested models. The test employs a hunt-and-test strategy:
    on a held-out hunt sample, it fits the null model and uses machine
    learning to find a direction in which the null model's score seems positive;
    on an independent test sample, it assesses the significance of the score in
    the hunted direction. The test employs orthogonalization to eliminate the
    bias from estimating the null model, yielding a test statistic that is
    asymptotically standard normal under the null without requiring a parametric
    form for the alternative. Methods are provided for 'glm', 'lm' and
    'mgcv::gam' fits as well as for detecting heterogeneous treatment effects.
    The methodology is described in Dhawan, Guo and Shah (2026)
    <doi:10.48550/arXiv.2607.28861>.
URL: https://unbiased.co.in/dScoreTest/,
        https://github.com/richardkwo/dScoreTest
BugReports: https://github.com/richardkwo/dScoreTest/issues
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
RoxygenNote: 7.3.3
Imports: grf, mgcv
Suggests: knitr, rmarkdown, speff2trial, testthat (>= 3.0.0)
Config/testthat/edition: 3
VignetteBuilder: knitr
Config/Needs/website: rmarkdown
NeedsCompilation: no
Packaged: 2026-08-20 12:12:54 UTC; ricguo
Author: F. Richard Guo [aut, cre, cph] (ORCID:
    <https://orcid.org/0000-0002-2081-7398>),
  Aditya Dhawan [aut]
Maintainer: F. Richard Guo <ricguo@umich.edu>
Repository: CRAN
Date/Publication: 2026-09-02 20:20:02 UTC
Built: R 4.6.0; ; 2026-09-02 20:34:06 UTC; unix
