ssLongFull {powerMediation} | R Documentation |
Sample size calculation for longitudinal study with 2 time point
Description
Sample size calculation for testing if mean changes for 2 groups are the same or not for longitudinal study with 2 time point.
Usage
ssLongFull(delta,
sigma1,
sigma2,
rho = 0.5,
alpha = 0.05,
power = 0.8)
Arguments
delta |
absolute difference of the mean changes between the two groups: |
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. |
Details
The sample size formula is based on Equation 8.30 on page 335 of Rosner (2006).
n=\frac{2\sigma_d^2 (Z_{1-\alpha/2} + Z_{power})^2}{\delta^2}
where \sigma_d = \sigma_1^2+\sigma_2^2-2\rho\sigma_1\sigma_2
, \delta=|\mu_1 - \mu_2|
,
\mu_1
is the mean change over time t
in group 1,
\mu_2
is the mean change over time t
in group 2,
\sigma_1^2
is the variance of baseline values within a treatment group,
\sigma_2^2
is the variance of follow-up values within a treatment group,
\rho
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 \mu_1 = \mu_2
.
Value
required sample size per group
Note
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.
Author(s)
Weiliang Qiu stwxq@channing.harvard.edu
References
Rosner, B. Fundamentals of Biostatistics. Sixth edition. Thomson Brooks/Cole. 2006.
See Also
ssLong
, powerLong
,
powerLongFull
.
Examples
# 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)