cusum: Creats a cusum chart and cusum log-likelihood chart

In meyera/rcusum: Tools for the easy creation cusum analysis charts

Description

Implementation of an unadjusted cusum chart and cusum log-likelihood chart as described in Rogers et al. (2004)

Usage

  cusum(failure_indicator, p0, p1, alpha = 0.01,
    beta = 0.01, by = NULL, loglike_chart = FALSE)

Arguments

failure_indicator	a numeric indicator variable consiting of only c(0,1), where 0 is no failure and 1 is failure for each procedure
p0	a constant representing the fixed acceptable event rate when the process is in control
p1	a constant representing the fixed unacceptable event rate we want to detect
alpha	Type I error (the probability of concluding that the failure rate has increased, when in fact it has not)
beta	Type II error (the probability of concluding that the failure rate has not increased, when in fact it has)
by	a factor vector consisting of the stratification variable.
loglike_chart	a flag controling which kind of chart will be shown

Value

an object of the class ggplot

Author(s)

Alexander Meyer

References

Rogers, C. A., Reeves, B. C., Caputo, M., Ganesh, J. S., Bonser, R. S., & Angelini, G. D. (2004). Control chart methods for monitoring cardiac surgical performance and their interpretation Chris. The Journal of Thoracic and Cardiovascular Surgery, 128(6), 811–819. doi:10.1016/j.jtcvs.2004.03.011

See Also

Other cusum: cusum.obs_minus_exp, cusum.sprt

Examples

set.seed(16)
df = data.frame(
 is_failure = c(rbinom(50,1,0.10),rbinom(50,1,0.08),rbinom(50,1,0.05),
                 rbinom(50,1,0.10),rbinom(50,1,0.13),rbinom(50,1,0.14),
                 rbinom(50,1,0.14),rbinom(50,1,0.09),rbinom(50,1,0.25)
 ),
 p0 = c(rnorm(50, 0.10, 0.03),rnorm(50, 0.10, 0.03),rnorm(50, 0.10, 0.03),
         rnorm(50, 0.10, 0.03),rnorm(50, 0.10, 0.03),rnorm(50, 0.10, 0.03),
         rnorm(50, 0.10, 0.03),rnorm(50, 0.15, 0.03),rnorm(50, 0.20, 0.03)
 ),
 by=rep(factor(c("Surgeon A", "Surgeon B", "Surgeon C")), times=c(150,150,150))
)
cusum_plot = cusum(df$is_failure, .10, .20, alpha=0.01,beta=0.01, loglike_chart=TRUE, by=df$by)
print(cusum_plot)
cusum_plot = cusum(df$is_failure, .10, .20, alpha=0.01,beta=0.01, loglike_chart=FALSE, by=df$by)
print(cusum_plot)

meyera/rcusum documentation built on May 22, 2019, 7:54 p.m.