Compare treatment effects at specific values of the moderator
inter.test(out, diff.values, percentile=FALSE, k=16)
an interflex object.
a numeric vector contain 2 or 3 elements which are within the range of the moderator. The treatment effects at corresponding values of the moderator will be compared.
a logical flag indicating whether to take values of the moderator on a percentile scale.
an integer specifying the dimension(s) of the bases used to represent the smooth term, default to 16.
Jens Hainmueller; Jonathan Mummolo; Yiqing Xu (Maintainer); Ziyi Liu
inter.test compare treatment effects at specific values of the moderator using marginal effects and vcov matrix derived from linear/kernel estimation. Based on GAM model(relies on mgcv package), users can approximate the treatment effect and its variance using smooth functions without re-estimating the model, hence saving time.
Jens Hainmueller; Jonathan Mummolo; Yiqing Xu. 2019. "How Much Should We Trust Estimates from Multiplicative Interaction Models? Simple Tools to Improve Empirical Practice." Political Analysis, Vol. 27, Iss. 2, April 2019, pp. 163--192. Available at: https://www.cambridge.org/core/journals/political-analysis/article/how-much-should-we-trust-estimates-from-multiplicative-interaction-models-simple-tools-to-improve-empirical-practice/D8CAACB473F9B1EE256F43B38E458706.
interflex, plot.interflex and predict.interflex