powerLongFull {powerMediation} | R Documentation |
Power calculation for longitudinal study with 2 time point
Description
Power calculation for testing if mean changes for 2 groups are the same or not for longitudinal study with 2 time point.
Usage
powerLongFull(delta,
sigma1,
sigma2,
n,
rho = 0.5,
alpha = 0.05)
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 |
n |
sample size per group |
rho |
correlation coefficient between baseline and follow-up values within a treatment group. |
alpha |
Type I error rate. |
Details
The power formula is based on Equation 8.31 on page 336 of Rosner (2006).
where ,
,
is the mean change over time
in group 1,
is the mean change over time
in group 2,
is the variance of baseline values within a treatment group,
is the variance of follow-up values within a treatment group,
is the correlation coefficient between baseline and follow-up values within a treatment group,
and
is the u-th percentile of the standard normal distribution.
We wish to test .
Value
power for testing for difference of mean changes.
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
, ssLongFull
,
powerLong
.
Examples
# 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)