Imputing Responder Proportions from Continuous Outcomes // 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.