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