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cff-version: 1.2.0
message: 'To cite package "DPI" in publications use:'
type: software
license: GPL-3.0-only
title: 'DPI: The Directed Prediction Index for Causal Direction Inference from Observational
  Data'
version: '2026.2'
doi: 10.32614/CRAN.package.DPI
abstract: The Directed Prediction Index ('DPI') is a causal discovery method for observational
  data designed to quantify the relative endogeneity of outcome (Y) versus predictor
  (X) variables in regression models. By comparing the coefficients of determination
  (R-squared) between the Y-as-outcome and X-as-outcome models while controlling for
  sufficient confounders and simulating k random covariates, it can quantify relative
  endogeneity, providing a necessary but insufficient condition for causal direction
  from a less endogenous variable (X) to a more endogenous variable (Y). Methodological
  details are provided at <https://psychbruce.github.io/DPI/>. This package also includes
  functions for data simulation and network analysis (correlation, partial correlation,
  and Bayesian Networks).
authors:
- family-names: Bao
  given-names: Han Wu Shuang
  email: baohws@foxmail.com
  orcid: https://orcid.org/0000-0003-3043-710X
repository: https://psychbruce.r-universe.dev
repository-code: https://github.com/psychbruce/DPI
commit: ded5a3244992f8455f7669aaa91a8d4342fa9b85
url: https://psychbruce.github.io/DPI/
date-released: '2026-02-25'
contact:
- family-names: Bao
  given-names: Han Wu Shuang
  email: baohws@foxmail.com
  orcid: https://orcid.org/0000-0003-3043-710X