FDRsamplesize2 (version 0.2.0)

average.power.coxph: Compute the average power of many Cox regression models

Description

Compute the average power of many Cox regression models for a given number of events, p-value threshold, vector of effect sizes (log hazard ratio),and variance of predictor variables

Usage

average.power.coxph(n, alpha, logHR, v)

Value

Average power estimate for multiple testing procedure

Arguments

n

number of events (scalar)

alpha

p-value threshold (scalar)

logHR

log hazard ratio (vector)

v

variance of predictor variable (vector)

References

Hsieh, FY and Lavori, Philip W (2000) Sample-size calculations for the Cox proportional hazards regression model with non-binary covariates. Controlled Clinical Trials 21(6):552-560.

See Also

power.cox for more details about power calculation of single-predictor Cox regression model. The power calculation is based on asymptotic normal approximation.

Examples

logHR = log(rep(c(1, 2),c(900, 100)));
v = rep(1, 1000);
average.power.coxph(n = 50, alpha = 0.05, logHR = logHR, v = v)