Packaged: 2022-04-17 18:42:17 UTC; ben.woodard

Imports: assertthat, httr, magrittr, purrr, R6, dplyr, tidyr, jsonlite,
glue, jose, tibble, lubridate, progress, vctrs, stringr, rlang,
Packaged: 2022-04-18 14:17:47 UTC; ben.woodard

Title: Heterogeneous Effects Analysis of Conjoint Experiments
Description: A tool for analyzing conjoint experiments using Bayesian Additive Regression Trees ('BART'), a machine learning method developed by Chipman, George and McCulloch (2010) <doi:10.1214/09-AOAS285>. This tool focuses specifically on estimating and visualizing the heterogeneity within marginal component effects, at the observation- and individual-level.
Suggests: testthat, knitr, cregg, rmarkdown

Description: A tool for analyzing conjoint experiments using Bayesian Additive Regression Trees ('BART'), a machine learning method developed by Chipman, George and McCulloch (2010) <doi:10.1214/09-AOAS285>. This tool focuses specifically on estimating, identifying, and visualizing the heterogeneity within marginal component effects, at the observation- and individual-level. It uses a variable importance measure ('VIMP') with delete-d jackknife variance estimation, following Ishwaran and Lu (2019) <doi:10.1002/sim.7803>, to obtain bias-corrected estimates of which variables drive heterogeneity in the predicted individual-level effects.
Imports: stats, rlang, tidyr, ggplot2, Rdpack, randomForestSRC

Imports: stats, rlang, tidyr, ggplot2, randomForestSRC, Rdpack

Packaged: 2022-03-02 11:00:42 UTC; tomrobinson

Title: AMCE Estimator for Conjoint Experiments
Author: Anton Strezhnev, Jens Hainmueller, Daniel Hopkins, Teppei Yamamoto
Depends: R (>= 2.0.0), sandwich, lmtest, ggplot2
Description: An R implementation of 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.

Author: Anton Strezhnev, Elissa Berwick, Jens Hainmueller, Daniel Hopkins, Teppei Yamamoto
Depends: R (>= 2.0.0), sandwich, lmtest, ggplot2, survey