README.md
In cgrcusum: Continuous Time Generalized Rapid Response CUSUM

cgrcusum

The goal of the cgrcusum 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.

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

install.packages("cgrcusum")

And the development version from GitHub with:

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

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

library(cgrcusum)
library(survival)
tdat <- subset(surgerydat, Hosp_num == 1)
tcbaseh <- function(t) chaz_exp(t, lambda = 0.01)
varsanalysis <- c("age", "sex", "BMI")
exprfit <- as.formula(paste("Surv(survtime, censorid) ~" ,paste(varsanalysis, collapse='+')))
tcoxmod <- coxph(exprfit, data= surgerydat)
#Alternatively, cbaseh can be left empty when specifying coxphmod through coxph()
cgr <- cgrcusum(data = tdat, coxphmod = tcoxmod, cbaseh = tcbaseh, pb = TRUE)
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plot(cgr)

You can plot the figure with control limit h = 3 by using:

plot(cgr, h = 3)

And determine the runlength of the chart when using control limit h = 4:

runlength(cgr, h = 4)
#> [1] 102

Hospital 1 would be detected by a CGR-CUSUM with control limit h = 4 after 102 days.

Alternatively, you can construct the CGR-CUSUM only until it crosses control limit h = 3 by:

cgr <- cgrcusum(data = tdat, coxphmod = tcoxmod, cbaseh = tcbaseh, pb = TRUE, h = 3)
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plot(cgr)