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) . 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 Roxygen: list(markdown = TRUE) 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 Config/pak/sysreqs: make Repository: https://richardkwo.r-universe.dev Date/Publication: 2026-08-05 22:23:07 UTC RemoteUrl: https://github.com/richardkwo/dscoretest RemoteRef: HEAD RemoteSha: bda20925f496e5c53c98b3f1a0379fd9fd939c60 NeedsCompilation: no Packaged: 2026-09-19 10:46:46 UTC; root Author: F. Richard Guo [aut, cre, cph] (ORCID: ), Aditya Dhawan [aut] Maintainer: F. Richard Guo