https://sanderroberti.r-universe.devRecent package updates in sanderrobertiR-universehttps://github.com/sanderroberti.pnghttps://sanderroberti.r-universe.devFri, 12 Jun 2026 22:42:50 GMTsander.roberti@nih.gov (Sander Roberti)Analyze association studies with multiple realizations of a noisy or uncertain exposure. These can be obtained from e.g. a two-dimensional Monte Carlo dosimetry system (Simon et al 2015 <doi:10.1667/RR13729.1>) to characterize exposure uncertainty. The implemented methods are regression calibration (Carroll et al. 2006 <doi:10.1201/9781420010138>), extended regression calibration (Little et al. 2023 <doi:10.1038/s41598-023-42283-y>), Monte Carlo maximum likelihood (Stayner et al. 2007 <doi:10.1667/RR0677.1>), frequentist model averaging (Kwon et al. 2023 <doi:10.1371/journal.pone.0290498>), and Bayesian model averaging (Kwon et al. 2016 <doi:10.1002/sim.6635>). Supported model families are Gaussian, binomial, multinomial, Poisson, proportional hazards, and conditional logistic.https://github.com/r-universe/sanderroberti/actions/runs/27448430804Fri, 12 Jun 2026 22:42:50 GMTameras0.4.0.9000successhttps://sanderroberti.r-universe.devhttps://github.com/sanderroberti/amerasconfidenceintervals.Rmdconfidenceintervals.htmlConfidence intervals2026-04-01 16:08:002026-06-12 16:28:03modelfitting.Rmdmodelfitting.htmlFitting models and displaying output2026-04-01 16:08:002026-06-12 16:28:03manualfma.Rmdmanualfma.htmlManual FMA from regression calibration fits2026-06-12 18:18:192026-06-12 18:18:19transformations.Rmdtransformations.htmlParameter transformations2026-04-01 16:08:002026-06-12 16:28:03relativeriskmodels.Rmdrelativeriskmodels.htmlRelative risk models2026-04-01 16:08:002026-06-12 16:28:03standardanalysis.Rmdstandardanalysis.htmlStandard analyses with one dose realization2026-06-12 16:55:152026-06-12 16:55:15