Following up on a recent blog article that discussed how to use R to explore your researcher degrees of freedom, this post introduces a specification curve plot as suggested in Simonsohn, Simmons and Nelson. With this plot, you can eyeball how various researcher degrees of freedom affect your main outcome of interest.
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.
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.