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CRTConjoint

The goal of CRTConjoint is to use the conditional randomization test (CRT) to test for various hypothesis in conjoint experiments. In particular, 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.

Installation

You can install CRTConjoint from GitHub with:

# install.packages("devtools")
devtools::install_github("daewoongham97/CRTConjoint")

or directly from CRAN with:

install.packages("CRTConjoint")

Example

This is a basic example which shows you how to test whether education matters for immigration preferences.

library(CRTConjoint)

# Immigration data
data("immigrationdata")
form = formula("Y ~ FeatEd + FeatGender + FeatCountry + FeatReason + FeatJob +
FeatExp + FeatPlans + FeatTrips + FeatLang + ppage + ppeducat + ppethm + ppgender")
left = colnames(immigrationdata)[1:9]
right = colnames(immigrationdata)[10:18]

## Not run: 
# Testing whether edcuation matters for immigration preferences
education_test = CRT_pval(formula = form, data = immigrationdata, X = "FeatEd",
 left = left, right = right, non_factor = "ppage", B = 100, analysis = 2)
education_test$p_val

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.