racusum_discretebeta_arl_sim: Compute ARLs of RA-CUSUM control charts using simulation

In vlad: Variable Life Adjusted Display and Other Risk-Adjusted Quality Control Charts

Description

Compute ARLs of RA-CUSUM control charts using simulation.

Usage

racusum_discretebeta_arl_sim(r, shape1, shape2, coeff, h, RA = 2, rs = 72,
  RQ = 1)

Arguments

r	Integer Vector. Number of runs.
shape1	Double. Shape parameter alpha > 0 of the beta distribution.
shape2	Double. Shape parameter beta > 0 of the beta distribution.
coeff	Numeric Vector. Estimated intercept and slope coefficients from a binary logistic regression model.
h	Double. Control Chart limit for detecting deterioration/improvement.
RA	Double. Odds ratio of death under the alternative hypotheses. Detecting deterioration in performance with increased mortality risk by doubling the odds Ratio RA = 2. Detecting improvement in performance with decreased mortality risk by halving the odds ratio of death RA = 1/2.
rs	Integer. Number of intervals between 0 and the maximum risk score.
RQ	Double. Defines the performance of a surgeon with the odds ratio ratio of death. Q.

Value

Returns a single value which is the Run Length.

Author(s)

Philipp Wittenberg

Examples

## Not run: 
library(vlad)
m <- 1e3
RLS <- sapply(1:m, racusum_discretebeta_arl_sim, shape1=1, shape2=3, coeff=c(-3.6798, 0.0768),
h=4.5, RA=2,  rs=71+1, RQ=1)
data.frame(cbind(ARL=mean(RLS), ARLSE=sd(RLS)/sqrt(m)))

## End(Not run)

vlad documentation built on Feb. 15, 2021, 5:12 p.m.