Hierarchical Signal Detection Theory Models for Unconscious Processing R package uSDT version 0.1.0 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'. Software Depends: R (>= 4.1) Imports: stats, utils, lme4, ggplot2, rlang Suggests: testthat (>= 3.0.0), knitr, rmarkdown Ricardo Rey-Sáez <ricardoreysaez95@gmail.com> Comprehensive R Archive Network (CRAN) Ricardo Rey-Sáez [aut, cre] (ORCID: <https://orcid.org/0000-0001-6739-2035>), Francisco Garre-Frutos [aut] (ORCID: <https://orcid.org/0000-0001-9810-186X>), Alicia Franco-Martínez [aut] (ORCID: <https://orcid.org/0000-0002-9710-1240>), Miguel Vadillo [aut] (ORCID: <https://orcid.org/0000-0001-8421-816X>) GPL-3 2026-09-29 application/tgz https://CRAN.R-project.org/package=uSDT doi:10.32614/CRAN.package.uSDT