replext_t3_c5.2 | R Documentation |
This function is tailored to replicate and extend the statistical power analysis
from Table 3 cell block 5.2 in the paper by Dwivedi et al. (2017). It covers
scenarios with normal distribution, unequal sample sizes, and different variances
in the two groups. The function uses replext_t2_c1.1
for its calculations,
with adjusted means, variances, and sample sizes.
replext_t3_c5.2(
M1 = 5,
S1 = 1,
M2 = 7,
S2 = 3,
Sk1 = NULL,
Sk2 = NULL,
n1 = c(3, 4, 5, 6),
n2 = c(7, 11, 10, 9),
n_simulations = 10000,
nboot = 1000,
conf.level = 0.95
)
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 3. |
Sk1 |
Skewness parameter for the first group, default is NULL (normal distribution). |
Sk2 |
Skewness parameter for the second group, default is NULL (normal distribution). |
n1 |
Vector of sample sizes for the first group. |
n2 |
Vector of unequal sample sizes for the second group. |
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. |
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), indicating the power analysis.
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.
replext_t2_c1.1
replext_t3_c5.2(n1 = c(4), n2 = c(11), n_simulations = 1)
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