uSDT: Hierarchical Signal Detection Theory Models for Unconscious
Processing
Fits hierarchical signal detection theory (SDT) models to paired
direct and indirect measures, the design used to test for unconscious
processing. Continuous indirect measures (typically response times) are
dichotomized with the within-subject median split of Meyen et al. (2022)
<doi:10.1037/xge0001065> so that both tasks are placed on a common
sensitivity scale. The package estimates a binomial probit mixed model in
which the two sensitivities are correlated random effects, and tests the
three hypotheses of interest: the group-level difference between
sensitivities, their latent correlation, and the latent regression of the
indirect on the direct measure, whose intercept is the test for
unconscious processing. Frequentist estimation uses 'lme4'.
| Version: |
0.1.0 |
| Depends: |
R (≥ 4.1) |
| Imports: |
stats, utils, lme4, ggplot2, rlang |
| Suggests: |
testthat (≥ 3.0.0), knitr, rmarkdown |
| Published: |
2026-09-29 |
| DOI: |
10.32614/CRAN.package.uSDT (may not be active yet) |
| Author: |
Ricardo Rey-Sáez 
[aut, cre],
Francisco Garre-Frutos
[aut],
Alicia Franco-Martínez
[aut],
Miguel Vadillo
[aut] |
| Maintainer: |
Ricardo Rey-Sáez <ricardoreysaez95 at gmail.com> |
| BugReports: |
https://github.com/RicardoReySaez/uSDT/issues |
| License: |
GPL-3 |
| URL: |
https://github.com/RicardoReySaez/uSDT,
https://ricardoreysaez.github.io/uSDT/ |
| NeedsCompilation: |
no |
| Materials: |
README, NEWS |
| CRAN checks: |
uSDT results |
Documentation:
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