powerTOSTtwo {TOSTER} | R Documentation |
Power analysis for TOST for independent t-test (Cohen's d).
powerTOSTtwo(alpha, statistical_power, N, low_eqbound_d, high_eqbound_d)
alpha |
alpha used for the test (e.g., 0.05) |
statistical_power |
desired power (e.g., 0.8) |
N |
sample size per group (e.g., 108) |
low_eqbound_d |
lower equivalence bounds (e.g., -0.5) expressed in standardized mean difference (Cohen's d) |
high_eqbound_d |
upper equivalence bounds (e.g., 0.5) expressed in standardized mean difference (Cohen's d) |
Calculate either achieved power, equivalence bounds, or required N, assuming a true effect size of 0. Returns a string summarizing the power analysis, and a numeric variable for number of observations, equivalence bounds, or power.
Chow, S.-C., Wang, H., & Shao, J. (2007). Sample Size Calculations in Clinical Research, Second Edition - CRC Press Book. Formula 3.2.4 with k = 1
## Sample size for alpha = 0.05, 80% power, equivalence bounds of ## Cohen's d = -0.4 and Cohen's d = 0.4, assuming true effect = 0 powerTOSTtwo(alpha=0.05, statistical_power=0.8, low_eqbound_d=-0.4, high_eqbound_d=0.4) ## Statistical power for alpha = 0.05, N = 108 per group, equivalence bounds of ## Cohen's d = -0.4 and Cohen's d = 0.4, assuming true effect = 0 powerTOSTtwo(alpha=0.05, N=108, low_eqbound_d=-0.4, high_eqbound_d=0.4) ## Equivalence bounds for alpha = 0.05, N = 108 per group, statistical power of ## 0.8, assuming true effect = 0 powerTOSTtwo(alpha=0.05, N=108, statistical_power=0.8)