# success

# SUrvival Control
Chart EStimation Software

The goal of the package is to allow easy applications of continuous
time CUSUM procedures on survival data. Specifically, the Biswas &
Kalbfleisch CUSUM (2008) and the CGR-CUSUM (2021).

Besides this, it allows for the construction of the Binary CUSUM
chart and funnel plot on survival data as well.

## Installation

You can install the released version of success from CRAN with:

`install.packages("success")`

And the development version from GitHub with:

```
# install.packages("devtools")
devtools::install_github("d-gomon/success")
```

## CGR-CUSUM Example

This is a basic example which shows you how to construct a CGR-CUSUM
chart on a hospital from the attached data set “surgerydat”:

```
dat <- subset(surgerydat, unit == 1)
exprfit <- as.formula("Surv(survtime, censorid) ~ age + sex + BMI")
tcoxmod <- coxph(exprfit, data = surgerydat)
cgr <- cgr_cusum(data = dat, coxphmod = tcoxmod, stoptime = 200)
plot(cgr)
```

You can plot the figure with control limit by using:

And determine the runlength of the chart when using control limit
:

```
runlength(cgr, h = 10)
#> [1] 151
```

Hospital 1 would be detected by a CGR-CUSUM with control limit after days.

Alternatively, you can construct the CGR-CUSUM only until it crosses
control limit by:

```
cgr <- cgr_cusum(data = dat, coxphmod = tcoxmod, h = 10)
plot(cgr)
```

## References

The theory behind the methods in this package can be found in:

Gomon D., Putter H., Nelissen R.G.H.H., van der Pas S (2022): CGR-CUSUM: A Continuous
time Generalized Rapid Response Cumulative Sum chart, *arXiv: a
preprint*