ss.SLR.rho {powerMediation} | R Documentation |
Calculate sample size for testing slope for simple linear regression based on R2.
ss.SLR.rho(power, rho2, n.lower = 2.01, n.upper = 1e+30, alpha = 0.05, verbose = TRUE)
power |
power. |
rho2 |
square of the correlation between the outcome and the predictor. |
n.lower |
lower bound of the sample size. |
n.upper |
upper bound o the sample size. |
alpha |
type I error rate. |
verbose |
logical. TRUE means printing sample size; FALSE means not printing sample size.
|
The test is for testing the null hypothesis \lambda=0 versus the alternative hypothesis \lambda\neq 0 for the simple linear regressions:
y_i=\gamma+\lambda x_i + \epsilon_i, \epsilon_i\sim N(0, \sigma^2_{e})
n |
sample size. |
res.uniroot |
results of optimization to find the optimal sample size. |
The test is a two-sided test. Code for one-sided tests will be added later.
Weiliang Qiu stwxq@channing.harvard.edu
Dupont, W.D. and Plummer, W.D.. Power and Sample Size Calculations for Studies Involving Linear Regression. Controlled Clinical Trials. 1998;19:589-601.
minEffect.SLR
,
power.SLR
,
power.SLR.rho
,
ss.SLR.rho
.
ss.SLR.rho(power=0.8, rho2=0.6, alpha = 0.05, verbose = TRUE)