cjoint: A Package for Estimating Average Marginal Component-specific Effects for Conjoint Survey Experiments

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Description

This package allows researchers to estimate the causal effects of attributes in conjoint survey experiments. It implements the Average Marginal Component-specific Effects (AMCE) estimator presented in 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

Details

Package: cjoint
Type: Package
Version: 2.0
Date: 2015-07-22
License: GPL (>= 2)

Author(s)

Authors: Anton Strezhnev, Elissa Berwick, Jens Hainmueller, Daniel Hopkins, Teppei Yamamoto

Maintainer: Anton Strezhnev <astrezhnev@fas.harvard.edu>

References

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