ssMediation.VSMc.logistic {powerMediation} | R Documentation |
Sample size for testing mediation effect in logistic regression based on Vittinghoff, Sen and McCulloch's (2009) method
Description
Calculate sample size for testing mediation effect in logistic regression based on Vittinghoff, Sen and McCulloch's (2009) method.
Usage
ssMediation.VSMc.logistic(power,
b2,
sigma.m,
p,
corr.xm,
n.lower = 1,
n.upper = 1e+30,
alpha = 0.05,
verbose = TRUE)
Arguments
power |
power for testing |
b2 |
regression coefficient for the mediator |
sigma.m |
standard deviation of the mediator. |
p |
the marginal prevalence of the outcome. |
corr.xm |
correlation between the predictor |
n.lower |
lower bound for the sample size. |
n.upper |
upper bound for the sample size. |
alpha |
type I error rate. |
verbose |
logical. |
Details
The test is for testing the null hypothesis b_2=0
versus the alternative hypothesis b_2\neq 0
for the logistic regressions:
\log(p_i/(1-p_i))=b_0+b_1 x_i + b_2 m_i
Vittinghoff et al. (2009) showed that for the above logistic regression, testing the mediation effect
is equivalent to testing the null hypothesis H_0: b_2=0
versus the alternative hypothesis H_a: b_2\neq 0
.
The full model is
\log(p_i/(1-p_i))=b_0+b_1 x_i + b_2 m_i
The reduced model is
\log(p_i/(1-p_i))=b_0+b_1 x_i
Vittinghoff et al. (2009) mentioned that if confounders need to be included
in both the full and reduced models, the sample size/power calculation formula
could be accommodated by redefining corr.xm
as the multiple
correlation of the mediator with the confounders as well as the predictor.
Value
n |
sample size. |
res.uniroot |
results of optimization to find the optimal sample size. |
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
Vittinghoff, E. and Sen, S. and McCulloch, C.E.. Sample size calculations for evaluating mediation. Statistics In Medicine. 2009;28:541-557.
See Also
minEffect.VSMc.logistic
,
powerMediation.VSMc.logistic
Examples
# example in section 4 (page 545) of Vittinghoff et al. (2009).
# n=255
ssMediation.VSMc.logistic(power = 0.80, b2 = log(1.5), sigma.m = 1, p = 0.5,
corr.xm = 0.5, alpha = 0.05, verbose = TRUE)