Computation of power analysis for a Cox Regression estimate pertaining to a continuous covariate

The powerEpiCont function is located in the powerSurvEpi library which will need loading into your R session. The below is a reproduction of the details given here.

The Hazard ratio, for a continous covariate, could compare hazard rates at one sd above the mean to the hazard rate at the mean.

Examples
  # example in the EXAMPLE section (page 557) of Hsieh and Lavori (2000).
  # Hsieh and Lavori (2000) assumed one-sided test, 
  # while this implementation assumed two-sided test. 
  # Hence alpha=0.1 here (two-sided test) will correspond
  # to alpha=0.05 of one-sided test in Hsieh and Lavori's (2000) example.
  powerEpiCont.default(n = 107, theta = exp(1), sigma2 = 0.3126^2, 
    psi = 0.738, rho2 = 0.1837, alpha = 0.1)

Results from using in a R session are below:

R version 2.11.1 (2010-05-31)
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ISBN 3-900051-07-0

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> library(powerSurvEpi)
> png(filename="powerEpiCont.default_%03d_med.png", width=480, height=480)
> ### Name: powerEpiCont.default
> ### Title: Power Calculation for Cox Proportional Hazards Regression with
> ###   nonbinary covariates for Epidemiological Studies
> ### Aliases: powerEpiCont.default
> ### Keywords: survival design
> 
> ### ** Examples
> 
>   # example in the EXAMPLE section (page 557) of Hsieh and Lavori (2000).
>   # Hsieh and Lavori (2000) assumed one-sided test, 
>   # while this implementation assumed two-sided test. 
>   # Hence alpha=0.1 here (two-sided test) will correspond
>   # to alpha=0.05 of one-sided test in Hsieh and Lavori's (2000) example.
>   powerEpiCont.default(n = 107, theta = exp(1), sigma2 = 0.3126^2, 
+     psi = 0.738, rho2 = 0.1837, alpha = 0.1)
[1] 0.8064577
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
> 
>