| hettx-package | Fisherian and Neymanian Methods for Detecting and Measuring Treatment Effect Variation |
| coef.RI.regression.result | Extract coefficients of a fit RI regression model. |
| detect_idiosyncratic | detect_idiosyncratic |
| estimate_systematic | Calculate systematic effects model using LATE, ITT, or full potential outcomes. |
| get_p_value | get p-value along with uncertainty on p-value |
| glance.FRTCI.test | Glance at a FRTCI.test result |
| glance.RI.R2.result | Glance at an RI.R2.result |
| glance.RI.regression.result | Glance at an RI.regression.result |
| hettx | Fisherian and Neymanian Methods for Detecting and Measuring Treatment Effect Variation |
| KS_stat | KS_stat |
| make_linear_data | Generate dataset according to a linear model. |
| make_quadradic_data | Generate dataset according to a linear model. |
| make_randomized_compliance_dat | Generate fake data with noncompliance. |
| make_randomized_dat | Make fake data for simulations |
| make_skew_data | Generate dataset according to a linear model. |
| Penn46_ascii | Sample data set |
| plot.FRTCI.test | plot.FRTCI.test |
| plot.RI.R2.result | Make a plot of the treatment effect R2 estimates |
| R2 | Estimate treatment variation R2 |
| rq_stat | rq_stat |
| rq_stat_cond_cov | rq_stat |
| rq_stat_uncond_cov | rq_stat |
| SE | Extract the standard errors from a var-cov matrix. |
| SKS_pool_t | SKS_pool_t |
| SKS_stat | SKS_stat |
| SKS_stat_cov | SKS_stat_cov_pool |
| SKS_stat_cov_pool | SKS_stat_cov_pool |
| SKS_stat_cov_rq | SKS_stat_cov_rq |
| SKS_stat_int_cov | SKS_stat_int_cov_pool |
| SKS_stat_int_cov_pool | SKS_stat_int_cov_pool |
| test_stat_info | test_stat_info |
| tidy.FRTCI.test | Tidy a FRTCI.test result |
| tidy.RI.R2.result | Tidy an RI.R2.result |
| tidy.RI.regression.result | Tidy an RI.regression.result |
| ToyData | Toy data set |
| variance_ratio_test | Variance ratio test |
| vcov.RI.regression.result | Get vcov() from object. |
| WSKS_t | WSKS_t |