Simulate Multi-Group Comparison Data (ANOVA)

Generate data for a one-way ANOVA with fully specified group means and standard deviations. Designed so that aov(score ~ group, data = r$data) recovers the true group effects at large n.

Usage

simulate_anova(n, means, sds = 1, labels = NULL, seed = NULL)

Arguments

n

Integer or integer vector. If a single value, the per-group sample size (equal groups). If a vector, must have length equal to length(means) giving per-group sizes.

means

Numeric vector. Population mean for each group.

sds

Numeric scalar or vector. Standard deviation(s) for each group. Scalar is recycled. Default: 1.

labels

Character vector or NULL. Group labels. Default: paste0("G", seq_along(means)).

seed

Integer or NULL. Random seed.

Value

A saqr_sim object with:

$data

data.frame with columns group (factor) and score (numeric).

$params

list with means, sds (as vector), n (per-group sizes), labels, eta_squared (true population \(\eta^2\)).

Examples

r <- simulate_anova(n = 30, means = c(10, 12, 15), seed = 1)
summary(aov(score ~ group, data = r$data))
#>             Df Sum Sq Mean Sq F value Pr(>F)    
#> group        2  383.5   191.7   238.8 <2e-16 ***
#> Residuals   87   69.9     0.8                   
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
r$params$eta_squared
#> [1] 0.8137045

# Unequal groups and heteroscedastic
r2 <- simulate_anova(n = c(50, 30, 20), means = c(5, 5, 10),
                      sds = c(1, 2, 3), seed = 42)