chiragjp/quantvoe: Modeling vibrational effects in observational data

When computing any association between a X and a Y variable -- like coffee and heart attacks, wine and mortality, or weight and type 2 diabetes onset, different modeling strategies can often yield different results. We refer to this as "vibration of effects," and it permeates any field that uses observational data (which is most fields). We build this package to model vibration of effects, fitting hundreds, thousands, potentially millions of models to show exactly how consistent an association output is. Quant_voe can be used for everything from clinical to economic data to tackle this problem, moving observational data science towards consistent reproducibility.

install.packages("remotes")
remotes::install_github("chiragjp/quantvoe")