Debiased Score Tests for Goodness of Fit and Model Comparison
Overview
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.
- Added a citation for the method paper, Dhawan, Guo and Shah (2026), <arXiv:2607.28861>.
- Added more examples.
From NEWS.md in the release
Install
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- OK13 OKNow
- OK9 OK2026-09-04
Documentation
The repository also keeps web-only articles.
- Help pages
- 23 (1 internal)includes a package overview page
- Examples that run
- 100%11 run in a plain check
- Exported functions with examples
- 45%
- Documented parameters
- 90%
- Return-value docs
- 100%
- Help pages citing references
- 26%
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Checks run against github.com/richardkwo/dscoretest on 2026-10-22.
GitHub Pages site last deployed 2026-08-05
pkgdown site last built 2026-08-05, before release 1.0.0 (2026-09-02)
Dependencies
Installing dScoreTest adds 7 packages (6 with compiled code, 6.5 MB of source tarballs). Heaviest: Rcpp 1.8 MB, RcppEigen 1.7 MB, sandwich 1.4 MB.
Code & Tests
People & History
- 1.0.0Latest2026-09-02 · current release
- RR 4.6.0 released · 2026-04-24
Package metadata
- First published
- 2026-09-02
- Total releases
- 1 / 1 yrs
- License
- MIT + file LICENSE OSI
- Download size
- 263 KB
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