replext_t5_c2.3 {npboottprm}

Replicate and Extend Simulation Results for Paired Distributions with Varied Skewness and Standard Deviations

Description

replext_t5_c2.3 is a wrapper function around replext_t5_c1.1, specifically designed to replicate and extend the simulation results from Table 5 cell 2.3 of the paper by Dwivedi et al. (2017). It focuses on paired distributions that exhibit skew normal characteristics with differing skewness parameters and standard deviations for each group.

Usage

replext_t5_c2.3(
  M1 = 5,
  S1 = 1,
  M2 = 5,
  S2 = 3,
  Sk1 = 0.2,
  Sk2 = 0.8,
  correl = 0.8,
  n = c(3, 4, 5, 6, 7, 8, 9, 10, 15, 25),
  n_simulations = 10000,
  nboot = 1000,
  conf.level = 0.95
)

Arguments

M1

Mean for the first group, default is 5.

S1

Standard deviation for the first group, default is 1.

M2

Mean for the second group, default is 5.

S2

Standard deviation for the second group, default is 3.

Sk1

Skewness parameter for the first group, default is 0.2.

Sk2

Skewness parameter for the second group, default is 0.8.

correl

Correlation between the two groups, default is 0.8.

n

Vector of sample sizes for the paired groups.

n_simulations

Number of simulations to run, default is 10,000.

nboot

Number of bootstrap samples, default is 1000.

conf.level

Confidence level for calculating p-value thresholds, default is 0.95.

Value

A data frame with columns for each sample size and the proportions of significant p-values for each test (PT, NPBTT, WRST, PTT), focusing on variations in skewness and standard deviations between the groups.

References

Dwivedi AK, Mallawaarachchi I, Alvarado LA. Analysis of small sample size studies using nonparametric bootstrap test with pooled resampling method. Stat Med. 2017 Jun 30;36(14):2187-2205. doi: 10.1002/sim.7263. Epub 2017 Mar 9. PMID: 28276584.

Examples

replext_t5_c2.3(n = c(10), n_simulations = 1)