persimon {npboottprmFBar}

Performance Simulation On Type I Error or Statistical Power

Description

Simulates performance (Type I Error or Statistical Power) for a range of statistical tests, including bootFbar, default setting restriktor::iht, and parametric bootstrap restriktor::iht. The function is set up to replicate the table structure in Dwivedi et al. (2017) Supplemental Tables 2 & 3.

Usage

persimon(
  M1 = 5,
  S1 = 1,
  M2 = 5,
  S2 = 1,
  M3 = 5,
  S3 = 1,
  Sk1 = NULL,
  Sk2 = NULL,
  Sk3 = NULL,
  n1 = c(2, 3, 4, 5, 6, 7, 8, 9, 10, 15),
  n2 = c(2, 3, 4, 5, 6, 7, 8, 9, 10, 15),
  n3 = c(2, 3, 4, 5, 6, 7, 8, 9, 10, 15),
  n_simulations = 10000,
  nboot = 1000,
  conf.level = 0.95
)

Arguments

M1

Mean value for group 1.

S1

Standard deviation for group 1.

M2

Mean value for group 2.

S2

Standard deviation for group 2.

M3

Mean value for group 3.

S3

Standard deviation for group 3.

Sk1

Skewness parameter for group 1; NULL for normal distribution.

Sk2

Skewness parameter for group 2; NULL for normal distribution.

Sk3

Skewness parameter for group 3; NULL for normal distribution.

n1

Vector of sample sizes for group 1.

n2

Vector of sample sizes for group 2.

n3

Vector of sample sizes for group 3.

n_simulations

Number of simulations to run (default is 10000).

nboot

Number of bootstrap samples (default is 1000).

conf.level

Confidence level for the tests (default is 0.95).

Details

The persimon function generates data for three groups with specified mean, standard deviation, and skewness, and then applies a range of statistical tests to this data, simulating the process across a specified number of iterations to assess performance in terms of Type I Error or Statistical Power. The output mirrors the format of the supplemental tables in Dwivedi et al. (2017).

Value

A list of data frames. One with the proportions of rejecting the null hypothesis for each test and sample size combination, and the other with the number of models which did not produce errors for each combination.

References

Dwivedi, A. K., Mallawaarachchi, I., & Alvarado, L. A. (2017). Analysis of small sample size studies using nonparametric bootstrap test with pooled resampling method. Statistics in Medicine, 36(14), 2187–2205. https://doi.org/10.1002/sim.7263

Examples

set.seed(135)
persimon(M1 = 5, S1 = 1, M2 = 5, S2 = 1, M3 = 5, S3 = 1,
         n1 = 6, n2 = 6, n3 = 6, n_simulations = 2, nboot = 4,
         conf.level = 0.95)