powerTOSTtwo.raw {TOSTER} | R Documentation |
Power analysis for TOST for independent t-test (raw scores).
powerTOSTtwo.raw( alpha, statistical_power, N, sdpooled, low_eqbound, high_eqbound, delta = 0 )
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) |
sdpooled |
specify the pooled standard deviation |
low_eqbound |
lower equivalence bounds (e.g., -0.5) expressed in raw scale units (e.g., scalepoints) |
high_eqbound |
upper equivalence bounds (e.g., 0.5) expressed in raw scale units (e.g., scalepoints) |
delta |
hypothesized true value for the difference between the 2 means. Default is zero. |
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 -200 and 200 in raw ## units, assuming pooled standard deviation of 350, and assuming true effect = 0 powerTOSTtwo.raw(alpha=0.05,statistical_power=0.8,low_eqbound=-200,high_eqbound=200,sdpooled=350) ## Power for alpha = 0.05, N = 53 per group, equivalence bounds of ## -200 and 200 in raw units, assuming sdpooled = 350 and true effect = 0 powerTOSTtwo.raw(alpha=0.05, N=53, low_eqbound=-200, high_eqbound=200, sdpooled=350) ## Equivalence bounds for alpha = 0.05, N = 108 per group, statistical power of ## 0.8, assuming true effect = 0 powerTOSTtwo.raw(alpha=0.05, N=53, statistical_power=0.8, sdpooled=350)