Description Usage Arguments Details Value Note Author(s) References See Also Examples
View source: R/powerLongitudinal.R
Sample size 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 | ssLongFull(delta,
sigma1,
sigma2,
rho = 0.5,
alpha = 0.05,
power = 0.8)
|
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 |
rho |
correlation coefficient between baseline and follow-up values within a treatment group. |
alpha |
Type I error rate |
power |
power for testing for difference of mean changes. |
The sample size formula is based on Equation 8.30 on page 335 of Rosner (2006).
n=\frac{2σ_d^2 (Z_{1-α/2} + Z_{power})^2}{δ^2}
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.
required sample size per group
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
, powerLong
,
powerLongFull
.
1 2 3 | # Example 8.33 on page 336 of Rosner (2006)
# n=85
ssLongFull(delta=5, sigma1=15, sigma2=15, rho=0.7, alpha=0.05, power=0.8)
|
[1] 85
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