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Calculate the sample size needed for target ANOVA power

Source: R/power_n_calc.R
power_n_calc.Rd

Calculation-only search for the per-between-cell sample size needed to reach a requested power for a balanced factorial ANOVA design. Unlike power_n(), this function does not run simulations, fit ANOVA models, or call car; numerator degrees of freedom, denominator degrees of freedom, noncentrality, and calculated power are obtained directly from the balanced design.

Usage

power_n_calc(
  between = NULL,
  within = NULL,
  term,
  target_pes,
  power = 0.9,
  alpha = 0.05,
  n_start = NULL,
  n_max = 5000,
  gpower = FALSE,
  epsilon = 1
)

Arguments

between

Named integer vector of between-subject factor level counts, e.g. c(group = 2). Use NULL for no between-subject factors.

within

Named integer vector of within-subject factor level counts, e.g. c(time = 3, condition = 4). Use NULL for no within-subject factors.

term

Character scalar naming the ANOVA term to test, e.g. "group:time". Interaction terms are order-insensitive; "time:group" resolves to "group:time" when that is the design's factor order.

target_pes

Target partial eta squared for term.

power

Desired target power.

alpha

Significance threshold.

n_start

Starting sample size per between-subject cell, not a lower bound for the search. If NULL, starts from the smallest value with valid calculated-power degrees of freedom.

n_max

Maximum sample size per between-subject cell.

gpower

Logical; if TRUE, use the GPower-style noncentrality convention lambda = total_n * f^2. The default FALSE uses lambda = den_df * f^2. GPower's estimates can differ from target_pes, especially for small samples or terms with more degrees of freedom; a warning is issued when gpower = TRUE. The default gpower = FALSE is recommended.

epsilon

Population nonsphericity correction for the within-subject component of term. Must lie between the theoretical lower bound 1 / within_term_df and 1. The default 1 assumes sphericity. Values below 1 multiply the numerator degrees of freedom, denominator degrees of freedom, and noncentrality parameter. Nonsphericity corrections do not apply to purely between-subject terms.

Value

An anovapowersim_curve object with n_needed and total_n_needed. The $results tibble contains n_per_cell, total_n, n_sims, valid_sims, failed_sims, numerator and denominator degrees of freedom (num_df, den_df), the nonsphericity correction (epsilon), the noncentrality parameter (ncp), calculated power (power_calc), and simulated power (power_sim). For power_n_calc(), the simulation-specific columns are always NA. When epsilon < 1, num_df and den_df are the corrected degrees of freedom used in the power calculation.

Lifecycle

[Experimental]

power_n_calc() is experimental while the calculated-power search API and reporting format are refined.

Examples

power_n_calc(
  between = c(cond = 2),
  within = c(stim = 4),
  term = "cond:stim",
  target_pes = 0.14,
  power = 0.90,
  epsilon = 0.70
)
#> <anovapowersim_curve>
#>   term:          'cond:stim'
#>   target power:  0.900
#>   alpha:         0.05
#>   effect size:   pes = 0.14
#>   n values:      9 per-cell sample sizes visited
#>   calculation:   calculated power only
#>   epsilon:       0.7
#>   n needed for between-subjects cell: 21
#>   total N needed: 42
#> 
#>  n_per_cell total_n n_sims valid_sims failed_sims epsilon num_df den_df    ncp
#>           2       4     NA         NA          NA     0.7    2.1    4.2  0.684
#>           4       8     NA         NA          NA     0.7    2.1   12.6  2.051
#>           8      16     NA         NA          NA     0.7    2.1   29.4  4.786
#>          16      32     NA         NA          NA     0.7    2.1   63.0 10.256
#>          20      40     NA         NA          NA     0.7    2.1   79.8 12.991
#>          21      42     NA         NA          NA     0.7    2.1   84.0 13.674
#>          22      44     NA         NA          NA     0.7    2.1   88.2 14.358
#>          24      48     NA         NA          NA     0.7    2.1   96.6 15.726
#>          32      64     NA         NA          NA     0.7    2.1  130.2 21.195
#>  power_calc power_sim
#>       0.077      <NA>
#>       0.185      <NA>
#>       0.436      <NA>
#>       0.799      <NA>
#>       0.892      <NA>
#>       0.908      <NA>
#>       0.922      <NA>
#>       0.945      <NA>
#>       0.987      <NA>