View source: R/powerTOSTpaired.R
powerTOSTpaired | R Documentation |
Power analysis for TOST for dependent t-test (Cohen's dz). This function is no longer maintained please use power_t_TOST.
powerTOSTpaired(alpha, statistical_power, N, low_eqbound_dz, high_eqbound_dz)
powerTOSTpaired.raw(
alpha,
statistical_power,
low_eqbound,
high_eqbound,
sdif,
N
)
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) |
low_eqbound_dz |
lower equivalence bounds (e.g., -0.5) expressed in standardized mean difference (Cohen's dz) |
high_eqbound_dz |
upper equivalence bounds (e.g., 0.5) expressed in standardized mean difference (Cohen's dz) |
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 |
sdif |
standard deviation of the difference scores |
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
## Cohen's dz = -0.3 and Cohen's d = 0.3, and assuming true effect = 0
powerTOSTpaired(alpha=0.05,statistical_power=0.8,low_eqbound_dz=-0.3,high_eqbound_dz=0.3)
## Sample size for alpha = 0.05, N = 96 pairs, equivalence bounds of
## Cohen's dz = -0.3 and Cohen's d = 0.3, and assuming true effect = 0
powerTOSTpaired(alpha=0.05,N=96,low_eqbound_dz=-0.3,high_eqbound_dz=0.3)
## Equivalence bounds for alpha = 0.05, N = 96 pairs, statistical power of
## 0.8, and assuming true effect = 0
powerTOSTpaired(alpha=0.05,N=96,statistical_power=0.8)
## 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
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