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

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.

1 | ```
calcVEt(object, nexposure, newdata, CIlevel = 0.95)
``` |

`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. |

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.

`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. |

Bin Yao, Ying Huang and Chaeryon Kang

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.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ```
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)
``` |

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