TLISI 2022: Simulations for Statistics: R Shiny Dashboards
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Leydier, Beatrice
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Our session will showcase interactive dashboards developed in R Shiny aimed as tools for students to understand statistical concepts with simulations. Developed to accompany a course introducing students to econometrics concepts like selection bias, RCT (Randomized Controlled Trial) design or Diff-in-Diff estimation, they can be used independently by students outside of the classroom or as a demonstration tool during a lecture alike. They allow users to generate and explore simulated datasets with set parameters the user can change. Each dashboard takes the user through a three step process: (1) generate a universe of observations and outcomes with the set parameters, (2) observe how the change in parameters affect the universe's data and the results of the model, (3) iterate this process n times and observe where the results fall on average for that given set of parameters, when repeated. This simulation approach leverages the interactive nature of online tools like R Shiny dashboards to provide a concrete, hands-on understanding of statistical concepts by going through multiple examples varying one parameter at a time, and helping students connect abstract concepts to a more familiar reality. It also intuitively introduces students to the concept of repeated draws by taking the examples through an iterative process and plotting estimates of the resulting models, which is an important concept underlying hypothesis testing. The dashboards we have developed cover the following concepts: (1) Selection Bias, (2) RCT sample size effects, (3) Difference-in-Difference estimates and assumptions, (4) Instrument Variable estimates and assumptions, (5) Regression Discontinuity estimates and assumptions. More tools can be developed to cover different concepts with a similar approach, or tackle other questions around these concepts, using the simulated data and estimates.
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http://hdl.handle.net/10822/1065375Rights
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