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FactorHet  

Estimate Heterogeneous Effects in Factorial Experiments Using Grouping and Sparsity
View on CRAN: Click here


Download and install FactorHet package within the R console
Install from CRAN:
install.packages("FactorHet")

Install from Github:
library("remotes")
install_github("cran/FactorHet")

Install by package version:
library("remotes")
install_version("FactorHet", "1.0.0")



Attach the package and use:
library("FactorHet")
Maintained by
Max Goplerud
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-01-20
Latest Update: 2025-01-13
Description:
Estimates heterogeneous effects in factorial (and conjoint) models. The methodology employs a Bayesian finite mixture of regularized logistic regressions, where moderators can affect each observation's probability of group membership and a sparsity-inducing prior fuses together levels of each factor while respecting ANOVA-style sum-to-zero constraints. Goplerud, Imai, and Pashley (2024) <doi:10.48550/ARXIV.2201.01357> provide further details.
How to cite:
Max Goplerud (2025). FactorHet: Estimate Heterogeneous Effects in Factorial Experiments Using Grouping and Sparsity. R package version 1.0.0, https://cran.r-project.org/web/packages/FactorHet. Accessed 06 Mar. 2026.
Previous versions and publish date:
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Complete documentation for FactorHet
Functions, R codes and Examples using the FactorHet R package
Full FactorHet package functions and examples
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