Model-Based Anomaly Detection for Repeat Test-Takers R package retestR version 0.1.0 Flags repeat test-takers whose second-attempt performance departs from what a growth model predicts, using independent evidence sources: model-expected score gain (accounting for regression to the mean, time between attempts and remediation), differential performance on exposed versus new items (Sinharay, 2017, <doi:10.3102/1076998616673872>), and differential response speed under a lognormal response-time model (van der Linden, 2006, <doi:10.3102/10769986031002181>). Evidence is combined into a risk index calibrated by parametric bootstrap under the no-misconduct model, so flagging thresholds carry explicit false-positive rates. Software Depends: R (>= 4.1) Imports: stats, utils Suggests: knitr, markdown Daniel Edi <danieledi2026@gmail.com> Comprehensive R Archive Network (CRAN) Daniel Edi [aut, cre, cph] (ORCID: <https://orcid.org/0000-0001-5475-819X>) MIT + file LICENSE (https://CRAN.R-project.org/package=retestR/LICENSE) 2026-10-08 application/tgz https://CRAN.R-project.org/package=retestR doi:10.32614/CRAN.package.retestR