Description Usage Arguments Details Value Note Author(s) References See Also Examples
View source: R/powerLongitudinal.R
Power calculation for testing if mean changes for 2 groups are the same or not for longitudinal study with 2 time point.
1 2 3 4 5 6 | powerLongFull(delta,
sigma1,
sigma2,
n,
rho = 0.5,
alpha = 0.05)
|
delta |
absolute difference of the mean changes between the two groups: δ=|μ_1 - μ_2| where μ_1 is the mean change over time t in group 1, μ_2 is the mean change over time t in group 2. |
sigma1 |
the standard deviation of baseline values within a treatment group |
sigma2 |
the standard deviation of follow-up values within a treatment group |
n |
sample size per group |
rho |
correlation coefficient between baseline and follow-up values within a treatment group. |
alpha |
Type I error rate. |
The power formula is based on Equation 8.31 on page 336 of Rosner (2006).
power=Φ≤ft(-Z_{1-α/2}+\frac{δ√{n}}{σ_d √{2}}\right)
where σ_d = σ_1^2+σ_2^2-2ρσ_1σ_2, δ=|μ_1 - μ_2|, μ_1 is the mean change over time t in group 1, μ_2 is the mean change over time t in group 2, σ_1^2 is the variance of baseline values within a treatment group, σ_2^2 is the variance of follow-up values within a treatment group, ρ is the correlation coefficient between baseline and follow-up values within a treatment group, and Z_u is the u-th percentile of the standard normal distribution.
We wish to test μ_1 = μ_2.
power for testing for difference of mean changes.
The test is a two-sided test. For one-sided tests, please double the
significance level. For example, you can set alpha=0.10
to obtain one-sided test at 5% significance level.
Weiliang Qiu stwxq@channing.harvard.edu
Rosner, B. Fundamentals of Biostatistics. Sixth edition. Thomson Brooks/Cole. 2006.
ssLong
, ssLongFull
,
powerLong
.
1 2 3 | # Example 8.33 on page 336 of Rosner (2006)
# power=0.80
powerLongFull(delta=5, sigma1=15, sigma2=15, n=85, rho=0.7, alpha=0.05)
|
[1] 0.8010713
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