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).
| Package: | factorEx |
| Type: | Package |
| Version: | 1.0.0 |
| Date: | 2019-09-22 |
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<U+2013>540. Available at https://scholar.princeton.edu/sites/default/files/negami/files/causalint.pdf.