Conducts sensitivity analyses for unmeasured confounding in random-effects meta-analysis per Mathur & VanderWeele (in preparation). Given output from a random-effects meta-analysis with a relative risk outcome, computes point estimates and inference for: (1) the proportion of studies with true causal effect sizes more extreme than a specified threshold of scientific significance; and (2) the minimum bias factor and confounding strength required to reduce to less than a specified threshold the proportion of studies with true effect sizes of scientifically significant size. Creates plots and tables for visualizing these metrics across a range of bias values. Provides tools to easily scrape study-level data from a published forest plot or summary table to obtain the needed estimates when these are not reported.