Building on our current working paper, and using ‘fancy’ animations, we (David Veenman and Joachim Gassen) discuss the issues related to non-random outliers in empirical archival research work and whether robust regression methods can be viewed as a panacea (spoiler: they can’t). Building on these insights we suggest a work-flow for archival work that helps us to take outlier treatment to the next level.

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I recently included the new Our World in Data data on Covid-19 vaccination progress around the world in the {tidycovid19} package. What was meant to be a short info post for package users turned into a mini case on “outliers”. See for yourself

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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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Author's picture

Joachim Gassen

Curious researcher, passionate teacher and coding nerd.

Professor of accounting at Humboldt-Universität zu Berlin