factorEx provides design-based and model-based estimators for the population average marginal
component effects (the pAMCE) in factorial experiments, including conjoint analysis.
The package also implements a series of recommendations offered in de la Cuesta, Egami, and Imai (2019+)
and Egami and Imai (2019, JASA).
Naoki Egami, Brandon de la Cuesta, Kosuke Imai
Maintainer: Naoki Egami firstname.lastname@example.org
de la Cuesta, Egami, and Imai. (2019+). Improving the External Validity of Conjoint Analysis: The Essential Role of Profile Distribution. (Working Paper). Available at https://scholar.princeton.edu/sites/default/files/negami/files/conjoint_profile.pdf.
Egami and Imai. (2019). Causal Interaction in Factorial Experiments: Application to Conjoint Analysis. Journal of the American Statistical Association, Vol.114, No.526 (June), pp. 529–540. Available at https://scholar.princeton.edu/sites/default/files/negami/files/causalint.pdf.
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