pwr_coxph: Calculate Power for Cox Regression Model

In LucyMcGowan/survivalpwr: Power calculations for survival analyses

Description

Compute power of Cox proportional hazards model or determine parameters to obtain target power.

Usage

pwr_coxph(
  hr = NULL,
  eventprob = NULL,
  n = NULL,
  rsquare = 0,
  stddev = 0.5,
  sig_level = 0.05,
  power = NULL,
  alternative = c("two.sided", "less", "greater")
)

Arguments

hr	Hazard ratio for a one unit increase in the predictor of interest
eventprob	Probability that an uncensored event occurs
n	Sample size
rsquare	The percent of variation in the predictor of interest explained by other covariates expected to be adjusted for in the Cox regression model (Default = 0)
stddev	Standard deviation of the predictor of interest (Default = 0.5)
sig_level	Significance level. (Default = 0.05)
power	Power of the test
alternative	Character. The alternative hypothesis of the test. Must be "two.sided" (Default), "greater", or "less"

Details

Exactly one of the parameters n or power must be passed as NULL – that parameter is determined from the others.

Value

Object of class "power.htest", a list containing the parameters specified as well as the one computed.

References

Hsieh, FY, and Philip W Lavori. 2000. "Sample-Size Calculations for the Cox Proportional Hazards Regression Model with Nonbinary Covariates." Controlled Clinical Trials 21 (6): 552–60.

Latouche, Aurélien, Raphaël Porcher, and Sylvie Chevret. 2004. "Sample Size Formula for Proportional Hazards Modelling of Competing Risks." Statistics in Medicine 23 (21): 3263–74.

Schoenfeld, David A. 1983. "Sample-Size Formula for the Proportional-Hazards Regression Model." Biometrics, 499–503.

Examples

## specify n to output the power
pwr_coxph(1.5, 0.8,  n = 80)

## specify power to output the sample size
pwr_coxph(1.5, 0.8, power = 0.8)

LucyMcGowan/survivalpwr documentation built on Dec. 17, 2021, 1:15 a.m.