Man pages for MRTSampleSizeBinary
Sample Size Calculator for MRT with Binary Outcomes
| alpha_1 | Vector that defines the success probability null curve. |
| beta_1 | Vector that defines the MEE under the alternative hypothesis. |
| compute_m_sigma | Computes "M" and "Sigma" matrices for the sandwich estimator... |
| compute_ncp | Computes the non-centrality parameter for an F distributed... |
| f_t_1 | A matrix defining the MEE under the alternative hypothesis. |
| g_t_1 | A matrix defining the success probability null curve. |
| is_full_column_rank | Check if a matrix is full column rank. |
| max_samp | Returns default maximum sample size to end power_vs_n_plot(). |
| min_samp | Compute minimum sample size. |
| m_matrix_1 | An example matrix for "bread" of sandwich estimator of... |
| mrt_binary_power | Calculate power for binary outcome MRT |
| mrt_binary_ss | Calculate sample size for binary outcome MRT |
| power_summary | Calculate sample size at a range of power levels. |
| power_vs_n_plot | Returns a plot of power vs sample size in the context of a... |
| p_t_1 | A vector of randomization probabilities for each time point. |
| sigma_matrix_1 | An example matrix for "meat" of sandwich estimator of... |
| tau_t_1 | Vector that holds the average availability at each time... |
