factorEx-package: factorEx: Design and Analysis for Factorial Experiments

In factorEx: Design and Analysis for Factorial Experiments

Description

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).

Details

Package:	factorEx
Type:	Package
Version:	1.0.0
Date:	2019-09-22

Author(s)

Naoki Egami, Brandon de la Cuesta, Kosuke Imai

Maintainer: Naoki Egami [e-mail]

References

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.

factorEx documentation built on July 2, 2020, 12:25 a.m.