Estimation, Diagnostics and Visualization of Conditional Marginal Effects

Performs estimation, diagnostics, and visualization of conditional marginal effects and group average treatment effects of a treatment on an outcome across different values of a moderator. Optionally integrates with the 'mlr3extralearners' package for additional machine learning backends compatible with the double machine learning estimators. 'mlr3extralearners' is not on CRAN but can be obtained from < https://github.com/mlr-org/mlr3extralearners>.


Reference manual

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install.packages("interflex")

1.4.1 by Yiqing Xu, 25 days ago


https://yiqingxu.org/packages/interflex/, https://github.com/xuyiqing/interflex


Report a bug at https://github.com/xuyiqing/interflex/issues


Browse source code at https://github.com/cran/interflex


Authors: Yiqing Xu [aut, cre] , Jens Hainmueller [aut] , Jonathan Mummolo [aut] , Tianzhu Qin [aut] , Jiehan Liu [aut] , Ziyi Liu [aut]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports ggplot2, sandwich, Lmoments, doFuture, doRNG, foreach, mgcv, lfe, gridExtra, grid, ggplotify, fixest, RColorBrewer, pcse, gtable, MASS, mvtnorm, pROC, ModelMetrics, lmtest, AER, future, splines, glmnet, grf, DoubleML, mlr3, mlr3learners, data.table, paradox, parallelly, cli, progressr

Suggests mlr3tuning, nnet, mlr3extralearners, lightgbm, xgboost, ranger, testthat


See at CRAN