| balanced_anova_design | Create a balanced factorial ANOVA design specification |
| cell_design | Define cells for a means-based unbalanced ANOVA design |
| compute_scale_factor | Compute the mean-deviation scaling factor from a change in partial eta squared |
| design_term_means | Build calibrated means for a design term |
| f_to_pes | Convert Cohen's f to partial eta squared |
| means_pattern | Define a sparse relative cell-mean pattern |
| plot_power_curve | Plot a simulation-based power curve |
| power_achieved | Estimate achieved ANOVA power at a fixed sample size |
| power_achieved_calc | Calculate achieved ANOVA power at a fixed sample size |
| power_curve | Simulate ANOVA power from a balanced factorial design |
| power_n | Search for the sample size needed for target ANOVA power |
| power_n_calc | Calculate the sample size needed for target ANOVA power |
| power_sensitivity | Estimate ANOVA effect-size sensitivity at a fixed sample size |
| power_sensitivity_calc | Calculate ANOVA effect-size sensitivity at a fixed sample size |
| power_unbalanced | Simulate power for a fixed unbalanced ANOVA design |
| print.anovapowersim_achieved_power | Print a fixed-sample achieved-power result |
| print.anovapowersim_curve | Print an anovapowersim power curve |
| print.anovapowersim_sensitivity | Print a fixed-sample sensitivity result |
| print.anovapowersim_unbalanced_power | Print simulated power for an unbalanced design |
| simulate_design_dataset | Simulate data from a balanced ANOVA design |
| summary.anovapowersim_achieved_power | Summarise a fixed-sample achieved-power result |
| summary.anovapowersim_curve | Summarise an anovapowersim power curve |
| summary.anovapowersim_sensitivity | Summarise a fixed-sample sensitivity result |
| summary.anovapowersim_unbalanced_power | Summarise simulated power for an unbalanced design |
| unbalanced_covariance | Specify covariance for a means-based unbalanced design |
| within_covariance | Specify a within-subject covariance structure |