Build calibrated default means for a design term

Creates the default contrast pattern for one ANOVA term and scales it so an exact reference dataset has the requested partial eta squared under the supplied balanced design assumptions.

Usage

design_term_means(
  design,
  term,
  target_pes,
  n,
  sd = 1,
  r = 0.5,
  gpower = FALSE,
  ss_type = "III"
)

Arguments

design

An anovapowersim_design_spec from balanced_anova_design().

term

Character scalar naming the ANOVA term to target. Interaction terms are order-insensitive.

target_pes

Target partial eta squared.

n

Sample size per between-subject cell. For pure within designs, this is the total sample size.

sd

Common outcome standard deviation.

r

Compound-symmetric correlation among within-subject cells.

gpower

Logical; if TRUE, calibrate to the G*Power-style noncentrality convention lambda = total_n * f^2 (using the 'as in Cohen (1988) option for within-subjects designs).

ss_type

Sums-of-squares type for the tested ANOVA term. "III" is the default for order-invariant tests in unbalanced designs. Use "I" to reproduce sequential stats::aov() tests.

Value

A numeric matrix of cell means, with rows indexing between cells and columns indexing within cells.

Examples

d <- balanced_anova_design(between = c(group = 2), within = c(time = 2))
design_term_means(d, term = "group:time", target_pes = 0.2, n = 20)
#>            [,1]       [,2]
#> [1,]  0.2436699 -0.2436699
#> [2,] -0.2436699  0.2436699