survSNP (version 0.26)

survSNP.power.table: Table for Asymptotic and Empirical Power

Description

This function produces a table with the resulting empirical and asymptotic power over a given range of Genotype Hazard Ratios, relative allelic frequencies, sample sizes, and event rates.

Usage

survSNP.power.table(GHRs, ns, rafs, erates, pilm, lm, model, test, alpha, 
                    exactvar = FALSE, B = 0)

Value

See output of sim.snp.expsurv.power.

Arguments

GHRs

A vector of Genotype Hazard Ratios

ns

A vector of sample sizes

rafs

A vector of relative allelic frequencies (for the risk allele)

erates

A vector of event rates

pilm

Probability that the time-to-event is greater than lm

lm

Landmark time used for powering the study

model

True genetic risk model (choices are "additive", "recessive" or "dominant". For the asymptotic calculations only the "additive" should be used until further notice)

test

Hypothesized genetic risk model (choices are "additive", "recessive" or "dominant". For the asymptotic calculations only the "additive" should be used until further notice)

alpha

Nominal two-sided type I error rate

exactvar

Indicator for using the exact variance formula

B

Number of simulation replicates (set to 0 if no empirical calculations are desired)

Author

Kouros Owzar, Zhiguo Li, Nancy Cox, Sin-Ho Jung and Chanhee Yi

Details

This version only supports additive models.

References

Kouros Owzar, Zhiguo Li, Nancy Cox and Sin-Ho Jung. Power and Sample Size Calculations for SNP Association Studies with Censored Time-to-Event Outcomes. https://onlinelibrary.wiley.com/doi/full/10.1002/gepi.21645

Examples

GRRs<-seq(1.5,2,by=0.25)
ns<-c(100,500,1000)
rafs<-c(0.3,0.5,0.7)
erates=c(0.5,0.7,0.9)
res<-survSNP.power.table(GRRs,ns,rafs,erates,pilm=0.5,lm=1,model="additive",
                         test="additive",alpha=0.05)

# Create key for illustration
KEY=paste("q=",levels(factor(res$raf)),sep="")
KEY<-list(lines=list(col=1:length(KEY),lty=1:length(KEY)),
          text=list(labels=paste("q=",levels(factor(res$raf)),sep="")),
          column=3)


# Illustrate Power
print(xyplot(pow0~GHR|factor(erate)*factor(n),group=factor(raf),
             data=res,type="l",lty=KEY$lines$lty,col=KEY$lines$col,
             key=KEY,
             xlab="Genotype Hazard Ratio",ylab="Power"))

# Illustrate Power (restricted to n=100)

print(xyplot(pow0~GHR|factor(erate),group=factor(raf),
             data=subset(res,n==ns[1]),
             type="l",lty=KEY$lines$lty,col=KEY$lines$col,
             key=KEY,
             xlab="Genotype Hazard Ratio",ylab="Power",
             sub=paste("n=",ns[1],", alpha=",round(unique(res$alpha),2))))