Fisherian and Neymanian Methods for Detecting and Measuring Treatment Effect Variation
Extract coefficients of a fit RI regression model.
detect_idiosyncratic
Calculate systematic effects model using LATE, ITT, or full potential ...
get p-value along with uncertainty on p-value
Fisherian and Neymanian Methods for Detecting and Measuring Treatment ...
KS.stat
Generate dataset according to a linear model.
Generate fake data with noncompliance.
Make fake data for simulations
plot.FRTCI.test
Make a plot of the treatment effect R2 estimates
Estimate treatment variation R2
rq.stat
Extract the standard errors from a var-cov matrix.
SKS.pool.t
SKS.stat.cov.pool
SKS.stat.cov.rq
SKS.stat.int.cov.pool
SKS.stat
test.stat.info
Variance ratio test
Get vcov() from object.
WSKS.t
Implements methods developed by Ding, Feller, and Miratrix (2016) <doi:10.1111/rssb.12124> <arXiv:1412.5000>, and Ding, Feller, and Miratrix (2018) <doi:10.1080/01621459.2017.1407322> <arXiv:1605.06566> for testing whether there is unexplained variation in treatment effects across observations, and for characterizing the extent of the explained and unexplained variation in treatment effects. The package includes wrapper functions implementing the proposed methods, as well as helper functions for analyzing and visualizing the results of the test.