power.cox: Compute the power of a single-predictor Cox regression model

In FDRsamplesize2: Computing Power and Sample Size for the False Discovery Rate in Multiple Applications

Compute the power of a single-predictor Cox regression model

Description

Use the formula of Hsieh and Lavori (2000) to compute the power of a single-predictor Cox model, which is based on asymptotic normal approximation.

Usage

power.cox(n, alpha, logHR, v)

Arguments

n	number of events (scalar)
alpha	p-value threshold (scalar)
logHR	log hazard ratio (vector)
v	variance of predictor variable (vector)

Value

Vector of power estimates for two-sided test

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.

Examples

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

FDRsamplesize2 documentation built on May 29, 2024, 7:12 a.m.