ss.SLR.rho: Sample size for testing slope for simple linear regression...
In powerMediation: Power/Sample Size Calculation for Mediation Analysis

Description Usage Arguments Details Value Note Author(s) References See Also Examples

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 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.