Imputing Responder Proportions from Continuous Outcomes R package respondeR version 0.1.0 Express meta-analyses of continuous trial outcomes in terms of responder risks, following the interpretability tutorial of Thorlund, Walter, Johnston, Furukawa and Guyatt (2011) <doi:10.1002/jrsm.46>. Given the mean change, standard deviation and sample size per arm across studies, respondeR estimates the proportion of patients who cross a minimal important difference (MID) threshold under a parametric model for the change scores, and contrasts the arms as a risk difference, risk ratio, odds ratio or number needed to treat. It provides median, unweighted-mean, weighted-mean and per-study (fixed- or random-effects) pooling, the standardized-mean-difference to odds-ratio bridge of Anzures-Cabrera, Sarpatwari and Higgins (2011) <doi:10.1002/sim.4298>, a threshold-free common-language effect size, and a point-and-click 'Shiny' application. The estimation methods were evaluated in a simulation study by Sofi-Mahmudi (2024) <https://hdl.handle.net/11375/30210>. Software Depends: R (>= 3.5) Imports: stats Suggests: shiny, shinydashboard, DT, testthat (>= 3.0.0), metafor, knitr, rmarkdown Ahmad Sofi-Mahmudi <a.sofimahmudi@gmail.com> Comprehensive R Archive Network (CRAN) Ahmad Sofi-Mahmudi [aut, cre] (ORCID: <https://orcid.org/0000-0001-6829-0823>) GPL-3 2026-06-19 application/tgz https://CRAN.R-project.org/package=respondeR doi:10.32614/CRAN.package.respondeR