Simulate a two-group design

Usage

simulate_ttest(
  n_a = 50L,
  n_b = 50L,
  mean_a = NULL,
  mean_b = NULL,
  sd_a = 1,
  sd_b = 1,
  labels = c("A", "B"),
  outcome = "outcome",
  seed = NULL,
  batch = NULL
)

Arguments

n_a, n_b: Group sample sizes, each defaulting to 50.
mean_a, mean_b: Group means. A mean left NULL (the default) is drawn from the standard normal distribution and rounded to two decimals, inside the same seeded draw as the data, and is reported in the parameters table.
sd_a, sd_b: Positive group standard deviations.
labels: Two group labels.
outcome: Name of the outcome variable.
seed: Optional random seed.
batch: Optional single positive whole number. When given, the simulator runs batch times and returns a plain list of batch results, each exactly what the same call without batch returns. With a seed, every dataset gets its own seed drawn from seed, so the whole batch is reproducible; without one the datasets are consecutive draws from the session's random-number stream. The default NULL returns a single result.

Value

A simulab_sim base data.frame with one row per observation and columns id, group and outcome (renamed by outcome). Two tidy tables come from as.data.frame(): what = "parameters" has one row per group with columns group, n, mean and sd; what = "effects" has a single row with columns contrast, mean_difference, pooled_sd and cohens_d, the population Cohen's d formed from the sample-size-weighted pooled standard deviation.

Examples

result <- simulate_ttest(n_a = 40, n_b = 40, mean_a = 0, mean_b = 0.6, seed = 1)
head(result)
#> <simulab_sim:ttest> 6 rows x 3 columns
#>   id group    outcome
#> 1  1     A -0.6264538
#> 2  2     A  0.1836433
#> 3  3     A -0.8356286
#> 4  4     A  1.5952808
#> 5  5     A  0.3295078
#> 6  6     A -0.8204684
#> 
#> Truth (parameters):
#>   group  n mean sd
#> 1     A 40  0.0  1
#> 2     B 40  0.6  1
#> 
#> Other tables: effects. Read one with as.data.frame(x, what = "effects").
as.data.frame(result, what = "parameters")
#>   group  n mean sd
#> 1     A 40  0.0  1
#> 2     B 40  0.6  1

# With no arguments, the group means are drawn and reported.
drawn <- simulate_ttest(seed = 1)
as.data.frame(drawn, what = "parameters")
#>   group  n  mean sd
#> 1     A 50 -0.63  1
#> 2     B 50  0.18  1