immigrationconjoint {cjoint}

Immigration Conjoint Experiment Dataset from Hainmueller et. al. (2014)

Description

A dataset containing the results of a conjoint survey of a representative sample of American adults who were asked to choose which hypothetical immigrants they think should be admitted into the United States. Each row corresponds to a single profile presented to the respondent.

Usage

data("immigrationconjoint")

Format

A data frame with 13,960 observations on the following 16 variables.

CaseID

a numeric vector indicating the respondent to which the particular profile corresponds

contest_no

a numeric vector indicating the number of the task to which the profile corresponds

Education

a factor with levels no formal, 4th grade, 8th grade, high school, two-year college, college degree, graduate degree

Gender

a factor with levels female, male

‘⁠Country of Origin⁠’

a factor with levels India, Germany, France, Mexico, Philippines, Poland, China, Sudan, Somalia, Iraq

‘⁠Reason for Application⁠’

a factor with levels reunite with family, seek better job, escape persecution

Job

a factor with levels janitor, waiter, child care provider, gardener, financial analyst, construction worker, teacher, computer programmer, nurse, research scientist, doctor

‘⁠Job Experience⁠’

a factor with levels none, 1-2 years, 3-5 years, 5+ years

‘⁠Job Plans⁠’

a factor with levels will look for work, contract with employer, interviews with employer, no plans to look for work

‘⁠Prior Entry⁠’

a factor with levels never, once as tourist, many times as tourist, six months with family, once w/o authorization

‘⁠Language Skills⁠’

a factor with levels fluent English, broken English, tried English but unable, used interpreter

Chosen_Immigrant

a numeric vector denoting whether the immigrant profile was selected

ethnocentrism

a numeric vector

profile

a numeric vector giving the profile number

LangPos

a numeric vector

PriorPos

a numeric vector

Source

Hainmueller, J., Hopkins, D., and Yamamoto T. (2014) Causal Inference in Conjoint Analysis: Understanding Multi-Dimensional Choices via Stated Preference Experiments. Political Analysis 22(1):1-30

Examples

## Not run: 
data("immigrationconjoint")
data("immigrationdesign")

# Run AMCE estimator using all attributes in the design
results <- amce(Chosen_Immigrant ~  Gender + Education + `Language Skills` + 
                `Country of Origin` + Job + `Job Experience` + `Job Plans` + 
                `Reason for Application` + `Prior Entry`, data=immigrationconjoint, 
                cluster=TRUE, respondent.id="CaseID", design=immigrationdesign)

## End(Not run)