Simple Power Simulations for ANOVAs


[Up] [Top]

Documentation for package ‘anovapowersim’ version 1.2.0

Help Pages

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