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Visualizing tidy, long data with multiple dimensions is a task often encountered when performing scientific computer simulations. In general, in such simulations the impact of many input variables on many outcome metrics is investigated. One area where such complex data structures containing the simulated data are encountered is clinical trial simulation. When visualizing the complex data, we are usually interested in the marginal effect of (one or several) input variables, which mostly renders existing visualization software useless or tedious to use. We have developed an R-Shiny app designed specifically for this task, which significantly speeds up the workflow. In this article, the app is described alongside two illustrative examples, one of which illustrates the use of the app for visualizing actual platform trial simulation data.