inst/doc/cusum.R

In cusum: Cumulative Sum (CUSUM) Charts for Monitoring of Hospital Performance

## ----setup, include = FALSE----------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.dim = c(7, 5)
)

library(cusum)

## ------------------------------------------------------------------------
data("cusum_example_data", package = "cusum")

head(cusum_example_data)

## ------------------------------------------------------------------------
data("racusum_example_data", package = "cusum")

head(racusum_example_data)

## ------------------------------------------------------------------------
cusum_example_p1 <- cusum_example_data[cusum_example_data$year == 2016, ]
cusum_example_p2 <- cusum_example_data[cusum_example_data$year == 2017, ]

racusum_example_p1 <- racusum_example_data[racusum_example_data$year == 2016, ]
racusum_example_p2 <- racusum_example_data[racusum_example_data$year == 2017, ]

## ------------------------------------------------------------------------
failure_probability <- mean(cusum_example_p1$y)

n_patients <- nrow(cusum_example_p1)

## ------------------------------------------------------------------------

cusum_limit <- cusum_limit_sim(failure_probability,
                               n_patients,
                               odds_multiplier = 2, 
                               n_simulation = 1000,
                               alpha = 0.05,
                               seed = 2046)


print(cusum_limit)

## ------------------------------------------------------------------------
patient_outcomes <- cusum_example_p2$y


cusum_cs <- cusum(failure_probability,
                  patient_outcomes,
                  limit = cusum_limit,
                  odds_multiplier = 2,
                  reset = FALSE)

head(cusum_cs)
plot(cusum_cs)

## ------------------------------------------------------------------------
cusum_cs <- cusum(failure_probability,
                  patient_outcomes,
                  limit = cusum_limit,
                  odds_multiplier = 2,
                  reset = TRUE)

plot(cusum_cs)

## ------------------------------------------------------------------------
n_patients <- nrow(cusum_example_p2)

cusum_alpha <- cusum_alpha_sim(failure_probability,
                               n_patients,
                               odds_multiplier = 2,
                               n_simulation = 1000,
                               limit = cusum_limit,
                               seed = 2046)

print(cusum_alpha)

## ------------------------------------------------------------------------

patient_risks <- racusum_example_p1$score

racusum_limit <- racusum_limit_sim(patient_risks,
                                   odds_multiplier = 2,
                                   n_simulation = 1000,
                                   alpha = 0.05,
                                   seed = 2046)

print(racusum_limit)

## ------------------------------------------------------------------------
patient_risks <- racusum_example_p2$score

patient_outcomes <- racusum_example_p2$y

racusum_cs <- racusum(patient_risks,
                      patient_outcomes,
                      limit = racusum_limit,
                      odds_multiplier = 2,
                      reset = FALSE)
plot(racusum_cs)

## ------------------------------------------------------------------------

racusum_cs <- racusum(patient_risks,
                      patient_outcomes,
                      limit = racusum_limit,
                      odds_multiplier = 2,
                      reset = TRUE)

plot(racusum_cs)

## ------------------------------------------------------------------------
racusum_alpha <- racusum_alpha_sim(patient_risks,
                                   odds_multiplier = 2,
                                   n_simulation = 1000,
                                   limit = racusum_limit,
                                   seed = 2046)

print(racusum_alpha)

## ------------------------------------------------------------------------

cusum_limit_improve <- cusum_limit_sim(failure_probability,
                                       n_patients,
                                       odds_multiplier = .5,
                                       n_simulation = 1000,
                                       alpha = 0.5,seed = 2046)

cusum_cs_improve <- cusum(failure_probability,
                          patient_outcomes = cusum_example_p2$y,
                          limit = cusum_limit_improve,
                          odds_multiplier = .5)

plot(cusum_cs_improve)

cusum_alpha_sim(failure_probability,
                n_patients,
                odds_multiplier = 0.5,
                n_simulation = 1000,
                limit = cusum_limit_improve,
                seed = 2046)