ss.SLR.rho {powerMediation}R Documentation

Sample size for testing slope for simple linear regression based on R2

Description

Calculate sample size for testing slope for simple linear regression based on R2.

Usage

ss.SLR.rho(power, rho2, n.lower = 2.01, n.upper = 1e+30, 
    alpha = 0.05, verbose = TRUE)

Arguments

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.

Details

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})

Value

n sample size.
res.uniroot results of optimization to find the optimal sample size.

Note

The test is a two-sided test. Code for one-sided tests will be added later.

Author(s)

Weiliang Qiu stwxq@channing.harvard.edu

References

Dupont, W.D. and Plummer, W.D.. Power and Sample Size Calculations for Studies Involving Linear Regression. Controlled Clinical Trials. 1998;19:589-601.

See Also

minEffect.SLR, power.SLR, power.SLR.rho, ss.SLR.rho.

Examples

  ss.SLR.rho(power=0.8, rho2=0.6, alpha = 0.05, verbose = TRUE)


[Package powerMediation version 0.0.6 Index]