hr.comp2: Function to statistically compare two hazard ratios...

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

Description

This function compares two hazard ratios from their betas and standard errors as computed by a Cox model for instance. The statistical test is a Student t test for dependent samples. The two hazard ratios must be computed from the same survival data.

Usage

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hr.comp2(x1, beta1, se1, x2, beta2, se2, n)

Arguments

x1

risk score used to estimate the first hazard ratio.

beta1

beta estimate for the first hazard ratio.

se1

standard error of beta estimate for the first hazard ratio.

x2

risk score used to estimate the second hazard ratio.

beta2

beta estimate for the second hazard ratio.

se2

standard error of beta estimate for the first hazard ratio.

n

number of samples from which the hazard ratios were estimated.

Details

The two hazard ratios must be computed from the same samples (and corresponding survival data). The function uses a Student t test for dependent samples.

Value

p.value

p-value from the Student t test for the comparison beta1 > beta2 (equivalently hr1 > hr2)

hr1

value of the first hazard ratio

hr2

value of the second hazard ratio

Author(s)

Benjamin Haibe-Kains

References

Student 1908) "The Probable Error of a Mean", Biometrika, 6, 1, pages 1–25.

Haibe-Kains, B. and Desmedt, C. and Sotiriou, C. and Bontempi, G. (2008) "A comparative study of survival models for breast cancer prognostication based on microarray data: does a single gene beat them all?", Bioinformatics, 24, 19, pages 2200–2208.

See Also

coxph, t.test

Examples

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set.seed(12345)
age <- as.numeric(rnorm(100, 50, 10) >= 50)
size <- as.numeric(rexp(100,1) > 1)
stime <- rexp(100)
cens <- runif(100,.5,2)
sevent <- as.numeric(stime <= cens)
stime <- pmin(stime, cens)
coxm1 <- coxph(Surv(stime, sevent) ~ age)
coxm2 <- coxph(Surv(stime, sevent) ~ size)
hr.comp2(x1=age, beta1=coxm1$coefficients, se1=drop(sqrt(coxm1$var)),
  x2=size, beta2=coxm2$coefficients, se2=drop(sqrt(coxm2$var)), n=100)

bhklab/survcomp documentation built on Dec. 26, 2021, 6:41 a.m.