calcVEt: Calculate Vaccine Efficacy Before or At the Time of Challenge...

In rld: Analyze and Design Repeated Low-Dose Challenge Experiments

Description

This function estimates the vaccine efficacy before or at the time of challenge t. VE(t)>0 indicates that the vaccine is effective in reducing the risk of infection before or at time t, whereas VE(t)<=0 indicate that the vaccine is not effective or has a negative effect.

Usage

calcVEt(object, nexposure, newdata, CIlevel = 0.95)

Arguments

object	a fitted object of class inheriting from "rld".
nexposure	a vector of challenges or exposures for all dose levels for predicting VE(t).
newdata	a data list for predicting vaccine efficacy where "contrgroup" and "refgroup" list names must be included.
CIlevel	the confidence level. The default is 0.95.

Details

Vaccine efficacy for preventing infection before or at the time of challenge t, VE(t), is defined as the relative reduction in the risk of infection before or at time t for the vaccine group compared to the placebo group. Please refer to Kang et al.(2015) for more details.

Value

VE	a vector containing vaccine efficacy estimates for contrast group and reference group.
se	a vector containing standard deviations of per-challenge vaccine efficacy estimates.
lwr	a vector containing lower bound of confidence interval for VE(t).
upr	a vector containing upper bound value of confidence interval for VE(t).
time	a vector containing challenge times.

Author(s)

Bin Yao, Ying Huang and Chaeryon Kang

References

Kang, C., Huang, Y., and Miller, C. (2015). A discrete-time survival model with random effects for designing and analyzing repeated low-dose challenge experiments. Biostatistics, 16(2): 295-310.

See Also

calcVEk, calcpk

Examples

data(SampleData)
augdata <- transdata(data = SampleData, ndlevel = 3, nexposure = c(10, 10, 2))
fitout <- rld(formula = survival::Surv(time, delta)~factor(dose)+trt+I(I(dose==3)*trt),
              data = augdata, frailty = TRUE)

contrgroup <- 1
refgroup <- 0
predata <- list(contrgroup, refgroup)
names(predata) <- c("contrgroup", "refgroup")
names(predata$contrgroup) <- c("trt")
names(predata$refgroup) <- c("trt")

VEtout <- calcVEt(object = fitout, nexposure = c(10, 10, 2), newdata = predata,
                  CIlevel = 0.95)
summary(VEtout)

rld documentation built on May 2, 2019, 5:57 a.m.