Reversing the predictor/response relationship
REGRESSION
It is typical in regression models to consider the hypothetically functionally antecedent variable as a predictor, independent or exogenous variable, rather than an outcome, dependent or endogenous variable. A counterexample is in outcome‐dependent sampling, such as in retrospective studies. We utilize the same strategy of reversing the typical predictor/response relationship, as is more convenient for modeling with high dimensional and complex quantities (such as brain connectivity) as the predictor. In the tDCS study, we model treatment assignment as the outcome using a logit model with the connectivity density and other covariates as the independent variables. This avoids the need to construct probability distributions on the connectivity densities themselves.To elaborate, using Bayes' rule and 