Online appendices detailing the robustness of empirical analyses are paramount but they never let readers explore all reasonable researcher degrees of freedom. Simonsohn, Simmons and Nelson suggest a ‘specification curve’ that allows readers to eyeball how the main coefficient of interest varies across a wide arrange of specifications. I build on this idea by making it interactive: A shiny-based web app enables readers to explore the robustness of findings in detail along the whole curve.

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Researchers face many options when designing tests. The resulting researcher degrees of freedom are often not well documented in published work but highly influential for findings. My new in-development R package rdfanaylsis provides a coding framework to systematically document and explore the researcher degrees of freedom in research designs based on observational data.

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Exploratory data analysis is important, everybody knows that. With R, it is also easy. Below you will see three lines of code that allow you to interactively explore the Preston Curve, the prominent association of country level real income per capita with life expectancy.

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Author's picture

Joachim Gassen

Curious researcher, passionate teacher and coding nerd.

Professor of accounting at Humboldt-Universit├Ąt zu Berlin

Berlin