Description Usage Arguments Details Value Note Author(s) References See Also Examples
View source: R/powerMediation.R
Calculate sample size for testing slope for simple linear regression.
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power |
power for testing if λ=0 for the simple linear regression y_i=γ+λ x_i + ε_i, ε_i\sim N(0, σ_{e}^2). |
lambda.a |
regression coefficient in the simple linear regression y_i=γ+λ x_i + ε_i, ε_i\sim N(0, σ_{e}^2). |
sigma.x |
standard deviation of the predictor sd(x). |
sigma.y |
marginal standard deviation of the outcome sd(y). (not the marginal standard deviation sd(y|x)) |
n.lower |
lower bound for the sample size. |
n.upper |
upper bound for the sample size. |
alpha |
type I error rate. |
verbose |
logical. |
The test is for testing the null hypothesis λ=0 versus the alternative hypothesis λ\neq 0 for the simple linear regressions:
y_i=γ+λ x_i + ε_i, ε_i\sim N(0, σ^2_{e})
n |
sample size. |
res.uniroot |
results of optimization to find the optimal sample size. |
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
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
.
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[1] 70.79538
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