The goal of CRTConjoint is to use the conditional randomization test
(CRT) to test for various hypothesis in conjoint experiments. In
CRT_pval aims to test whether a factor matters
in any way. For example, does education matter in immigration
preferences given other attributes of the candidate.
You can install CRTConjoint from GitHub with:
# install.packages("devtools") ::install_github("daewoongham97/CRTConjoint")devtools
or directly from CRAN with:
This is a basic example which shows you how to test whether education matters for immigration preferences.
library(CRTConjoint) # Immigration data data("immigrationdata") = formula("Y ~ FeatEd + FeatGender + FeatCountry + FeatReason + FeatJob + form FeatExp + FeatPlans + FeatTrips + FeatLang + ppage + ppeducat + ppethm + ppgender") = colnames(immigrationdata)[1:9] left = colnames(immigrationdata)[10:18] right ## Not run: # Testing whether edcuation matters for immigration preferences = CRT_pval(formula = form, data = immigrationdata, X = "FeatEd", education_test left = left, right = right, non_factor = "ppage", B = 100, analysis = 2) $p_valeducation_test