David BarangerinTowards Data ScienceInteraction analyses — Appropriately adjusting for control variablesOn inflated false-positives in interaction analyses, and how to get rid of them.May 27, 2020May 27, 2020
David BarangerResearchers want you to tell them how the pandemic has affected your mental healthThese projects will help us understand how covid-19 is reshaping the world, and will help health providers address this new reality.Mar 23, 2020Mar 23, 2020
David BarangerinThe StartupA quick intro to block permutations and bootstraps for analyzing hierarchical data…ignoring that your data is clustered could cause you miss significant effects.Nov 14, 2019Nov 14, 2019
David BarangerinThe StartupCorrelates of rock climbing abilityMy analysis of ‘what correlates with how well someone climbs?’.Oct 14, 2019Oct 14, 2019
David BarangerInteraction analyses — How large a sample do I need? (part 3)Determining what sample size is needed for an interaction.Sep 20, 2019Sep 20, 2019
David BarangerInteraction analyses — Interpreting effect sizes (part 2)Interpreting the effect-size of an interaction, by connecting it to simple-slopes.Sep 20, 2019Sep 20, 2019
David BarangerInteraction analyses — Power (part 1)How to do a power analysis for an interaction in a linear regression (in R), and what factors effect how much power you have.Sep 20, 20191Sep 20, 20191
David BarangerinTowards Data ScienceUsing the new Turbo palette from Google in RHow to quickly get started using Turbo with your ggplots.Aug 23, 20191Aug 23, 20191
David BarangerThe two-body problem: postdoc editionMy partner (soon to be wife!, Tayler) and I met while we were in the same PhD program. We are both interested in pursuing academic careers…Jul 30, 2018Jul 30, 2018
David BarangerImproving Genetic Prediction: Data cleaning & Meta-analysisImproving the last predictionApr 9, 2018Apr 9, 2018