## ----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)