rf_vimp: Estimate a Single Variable Importance Metric for 'cjbart'...

In cjbart: Heterogeneous Effects Analysis of Conjoint Experiments

Estimate a Single Variable Importance Metric for cjbart Object

Description

Estimates random forest variable importance scores for a single attribute-level of a conjoint experiment. This function is for advanced use. Users should typically use the het_vimp() function.

Usage

rf_vimp(model, outcome, covars = NULL)

Arguments

model	Object of class cjbart, the result of running IMCE()
outcome	Character string detailing the covariate over which to analyze heterogeneous effects
covars	An optional vector of covariates to include in the importance metric check. When covars = NULL (the default), all covariates are included in the importance model.

Value

Data.frame of variable importance scores for each covariate in the model, as well as values for the estimated 95% confidence interval for each importance score.

cjbart documentation built on Sept. 8, 2023, 5:57 p.m.