DPI: The Directed Prediction Index
The Directed Prediction Index ('DPI') is
a simulation-based and conservative method
for quantifying the relative endogeneity (relative dependence)
of outcome (Y) versus predictor (X) variables
in multiple linear regression models.
By comparing the proportion of variance explained (R-squared)
between the Y-as-outcome model and the X-as-outcome model
while controlling for a sufficient number
of potential confounding variables,
it suggests a more plausible influence direction
from a more exogenous variable (X) to a more endogenous variable (Y).
Methodological details are provided at
<https://psychbruce.github.io/DPI/>.
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