npboottprm (version 0.3.2)

replext_t3_c2.1: Replicate and Extend Statistical Power Analysis from Table 3 Cell 2.1

Description

This function is geared towards replicating and extending the statistical power analysis from Table 3 cell block 2.1 of the paper by Dwivedi et al. (2017). It deals with scenarios involving skewed distributions with equal variance and different means in the two groups. It acts as a wrapper around replext_t2_c1.1, with specific adjustments for skewness parameters and means.

Usage

replext_t3_c2.1(
  M1 = 5,
  S1 = 1,
  M2 = 7,
  S2 = 1,
  Sk1 = 0.8,
  Sk2 = 0.8,
  n1 = c(3, 4, 5, 6, 7, 8, 9, 10, 15, 25, 50, 100),
  n2 = c(3, 4, 5, 6, 7, 8, 9, 10, 15, 25, 50, 100),
  n_simulations = 10000,
  nboot = 1000,
  conf.level = 0.95
)

Value

A data frame with columns for each sample size pair (n1, n2) and the proportions of significant p-values for each test (ST, WT, NPBTT, WRST, PTT), reflecting the power analysis.

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 7.

S2

Standard deviation for the second group, default is 1.

Sk1

Skewness parameter for the first group, default is 0.8.

Sk2

Skewness parameter for the second group, default is 0.8.

n1

Vector of sample sizes for the first group.

n2

Vector of sample sizes for the second group, must be the same length as n1.

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.

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.

See Also

replext_t2_c1.1

Examples

replext_t3_c2.1(n1 = c(10), n2 = c(10), n_simulations = 1)