for problematic multicollinearity of 10. Final estimated coefficients were also graphically assessed for stability through comparison to the result from unweighted penalized logistic regression (specifically, a LASSO model) implemented with the glmnet package (Friedman et al., 2010). Penalized regression techniques like the LASSO are expected to be more robust than unconstrained models, and the estimated coefficients remained qualitatively consistent between techniques. This indicated that the chosen set of parameters was not unstable. We have presented our full collection of tests and used unmodified p-values, assessing statistical significance at the 0.05 level. As an exploratory study, we made no corrections for multiple tests.
