Simulate Experimental and Behavioural Data from a Portable Design Specification R package pilotr version 0.3.1 Generative simulation of experimental and behavioural data sets from a portable JavaScript Object Notation (JSON) design specification shared with the 'Python' package of the same name. Supports user-specified fixed effect sizes, crossed by-subject and by-item random intercepts and slopes, predictors measured with error, realistic response families (Gaussian, lognormal, shifted lognormal, ex-Gaussian, Bernoulli, Poisson, ordinal and Beta), and simulation-based power and precision-based design analysis, including the Type S and Type M errors of Gelman and Carlin (2014) <doi:10.1177/1745691614551642> and a region of practical equivalence. A shared cross-language random-number generator means that, given the same specification and seed, the R and 'Python' implementations produce identical data: exactly for the Gaussian family and for any family with rounding set, and to within the last unit in the last place for families applying a transcendental function to the linear predictor, whose rounding the IEEE-754 standard does not fix. Software Depends: R (>= 4.0.0) Imports: jsonlite, parallel, stats Suggests: shiny, future, promises, ggplot2 (>= 3.4.0), lme4, lmerTest, callr, knitr, rmarkdown, testthat (>= 3.0.0), MASS Pablo Bernabeu <pcbernabeu@gmail.com> Comprehensive R Archive Network (CRAN) Pablo Bernabeu [aut, cre] (ORCID: <https://orcid.org/0000-0003-1083-2460>) MIT + file LICENSE (https://CRAN.R-project.org/package=pilotr/LICENSE) 2026-09-20 application/tgz https://CRAN.R-project.org/package=pilotr doi:10.32614/CRAN.package.pilotr