| coef.rctglm | Methods for objects of class 'rctglm' |
| default_learners | Creates a list of learners |
| est | Methods for objects of class 'rctglm' |
| estimand | Methods for objects of class 'rctglm' |
| estimand.rctglm | Methods for objects of class 'rctglm' |
| fit_best_learner | Find the best learner in terms of RMSE among specified learners using cross validation |
| glm_data | Generate data simulated from a GLM |
| options | postcard Options |
| power_gs | Power and sample size estimation for linear models |
| power_linear | Power and sample size estimation for linear models |
| power_marginaleffect | Power approximation for estimating marginal effects in GLMs |
| power_nc | Power and sample size estimation for linear models |
| print.rctglm | Methods for objects of class 'rctglm' |
| prog | Extract information about the fitted prognostic model |
| prog.rctglm_prog | Extract information about the fitted prognostic model |
| rctglm | Fit GLM and find any estimand (marginal effect) using plug-in estimation with variance estimation using influence functions |
| rctglm_methods | Methods for objects of class 'rctglm' |
| rctglm_with_prognosticscore | Use prognostic covariate adjustment when fitting an rctglm |
| samplesize_gs | Power and sample size estimation for linear models |
| variance_ancova | Power and sample size estimation for linear models |