Draw Samples from a Gaussian Mixture Distribution — draw_sample

Draws exemplary samples with a certain effect size for the sequential one-oway ANOVA or the sequential t-test, see Steinhilber et al. (2023) doi:10.31234/osf.io/m64ne

Usage

draw_sample_mixture(k_groups, f, max_n, counter_n = 100, verbose = FALSE)

Arguments

k_groups: number of groups (levels of factor_A)
f: Cohen's f. The simulated effect size.
max_n: sample size for the groups (total sample size = max_n*k_groups)
counter_n: number of times the function tries to find a possible parameter combination for the distribution. Default value is set to 100.
verbose: TRUE or FALSE. Print out more information about the internal process of sampling the parameters (the internal counter that was reached, some additional hints and the drawn parameters for the Gaussian Mixture distributions.)

Value

returns a data.frame with the columns y (observations) and x (factor_A).

Examples

set.seed(333)

data <- sprtt::draw_sample_mixture(
  k_groups = 2,
  f = 0.40,
  max_n = 2
)
data
#>             y x
#> 1 -0.35195917 1
#> 2  0.65107923 2
#> 3  1.13464217 1
#> 4  0.06825929 2

data <- sprtt::draw_sample_mixture(
  k_groups = 4,
  f = 1.2, # very large effect size
  max_n = 4,
  counter_n = 1000, # increase of counter is necessary
  verbose = TRUE # prints more information to the console
)
#> Internal counter reached = 54
#> 
#> group1:
#> mean1 = -1.99074652277088, mean2 = -0.428610482246108,
#> sigma1 = 0.834923571040213, sigma2 = 0.287694501108814
#> 
#> group2:
#> mean1 = 1.23360638346966, mean2 = 0.129657848600828,
#> sigma1 = 1.05769847648328, sigma2 = 0.521462126165875
#> 
#> group3:
#> mean1 = -2.04772209975713, mean2 = -0.141818342492629,
#> sigma1 = 0.424153872448029, sigma2 = 0.0621202584498169
#> 
#> group4:
#> mean1 = 2.60899963472551, mean2 = 0.636633580470748,
#> sigma1 = 0.224572574962626, sigma2 = 0.0667325451814857
data
#>             y x
#> 1  -3.5762655 1
#> 2   0.7385727 2
#> 3  -0.1367248 3
#> 4   0.6237656 4
#> 5  -0.7708177 1
#> 6   1.0060454 2
#> 7  -1.7081033 3
#> 8   0.6918255 4
#> 9  -2.4084128 1
#> 10  0.1284941 2
#> 11 -1.9372623 3
#> 12  2.5216276 4
#> 13 -2.0195175 1
#> 14 -0.1744742 2
#> 15 -2.1017450 3
#> 16  0.6802637 4