EquiSurv (version 0.1.0)

confint_diff: Lower and upper confidence bounds for the difference of two parametric survival curves

Description

Function fitting parametric survival curves \(S_1\), \(S_2\) to two groups and yielding lower and upper (1-\(\alpha\))-confidence bounds for the difference \(S_1-S_2\) of these two curves at a specific time point, based on approximating the variance via bootstrap. For the bootstrap exponentially distributed random censoring is assumed and the parameters estimated from the datasets. \(m_1\) and \(m_2\) are parametric survival models following a Weibull, exponential, gaussian, logistic, log-normal or log-logistic distribution. For the generation of the bootstrap data exponentially distributed right-censoring is assumed and the rates estimated from the datasets. See Moellenhoff and Tresch <arXiv:2009.06699> for details.

Usage

confint_diff(alpha, t0, m1, m2, B = 1000, data_r, data_t, plot = TRUE)

Arguments

alpha

confidence level

t0

time point of interest

m1, m2

type of parametric model. Possible model types are "weibull", "exponential", "gaussian", "logistic", "lognormal" and "loglogistic"

B

number of bootstrap repetitions. The default is B=1000

data_r, data_t

datasets containing time and status for each individual (have to be referenced as this)

plot

if TRUE, a plot of the two survival curves will be given

Value

A list containing the difference \(S_1(t_0)-S_2(t_0)\), the lower and upper (1-\(\alpha\))-confidence bounds and a summary of the two model fits. Further a plot of the curves is given.

References

K.Moellenhoff and A.Tresch: Survival analysis under non-proportional hazards: investigating non-inferiority or equivalence in time-to-event data <arXiv:2009.06699>

Examples

# NOT RUN {
data(veteran)
veteran_r <- veteran[veteran$trt==1,]
veteran_t <- veteran[veteran$trt==2,]
alpha<-0.05
t0<-80
confint_diff(alpha=alpha,t0=t0,m1="weibull",m2="weibull",data_r=veteran_r,data_t=veteran_t)
# }