powerTOSTpaired.raw {TOSTER} | R Documentation |
Power analysis for TOST for dependent t-test (raw scores).
powerTOSTpaired.raw( alpha, statistical_power, N, sdif, low_eqbound, high_eqbound )
alpha |
alpha used for the test (e.g., 0.05) |
statistical_power |
desired power (e.g., 0.8) |
N |
number of pairs (e.g., 96) |
sdif |
standard deviation of the difference scores |
low_eqbound |
lower equivalence bounds (e.g., -0.5) expressed in raw mean difference |
high_eqbound |
upper equivalence bounds (e.g., 0.5) expressed in raw mean difference |
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 3.1.9
## Sample size for alpha = 0.05, 80% power, equivalence bounds of -3 and 3 in raw units ## and assuming a standard deviation of the difference scores of 10, and assuming a true effect = 0 powerTOSTpaired.raw(alpha=0.05,statistical_power=0.8,low_eqbound=-3, high_eqbound=3, sdif=10) ## Sample size for alpha = 0.05, N = 96 pairs, equivalence bounds of -3 and 3 in raw units ## and assuming a standard deviation of the difference scores of 10, and assuming a true effect = 0 powerTOSTpaired.raw(alpha=0.05,N=96,low_eqbound=-3, high_eqbound=3, sdif=10) ## Equivalence bounds for alpha = 0.05, N = 96 pairs, statistical power of 0.8 ## and assuming a standard deviation of the difference scores of 10, and assuming a true effect = 0 powerTOSTpaired.raw(alpha=0.05,N=96, statistical_power=0.8, sdif=10)