Robust Path Analysis

Robust path analysis is a statistical technique that applies robust estimation methods—such as sandwich standard errors or M-estimation—to path models, which specify directed causal relationships among observed variables. This approach ensures valid inference about path coefficients and indirect effects even when the data deviate from normality assumptions, contain outliers, or exhibit heteroscedasticity that would distort conventional standard errors.