Description Usage Arguments Value Author(s) References Examples
Compute CUSUM scores based on the log-likelihood ratio statistic.
1 | racusum_scores(wt1, wt2, reset = FALSE, h1 = NULL, h2 = NULL)
|
wt1 |
Double. Log-likelihood ratio scores from function |
wt2 |
Double. Log-likelihood ratio scores from function |
reset |
Logical. If |
h1 |
Double. Upper control limit of the CUSUM chart. |
h2 |
Double. Lower control limit of the CUSUM chart. |
Returns a list with two components for the CUSUM scores.
Philipp Wittenberg
Steiner SH, Cook RJ, Farewell VT and Treasure T (2000). Monitoring surgical performance using risk-adjusted cumulative sum charts. Biostatistics, 1(4), pp. 441-452.
Parsonnet V, Dean D, Bernstein AD (1989). A method of uniform stratification of risk for evaluating the results of surgery in acquired adult heart disease. Circulation, 79(6):I3-12.
Rigdon SE and Fricker RD (2015). Health Surveillance. In Chen DG and Wilson J (eds) Innovative Statistical Methods for Public Health Data, pp. 203–249. Springer, Cham.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 | ## Not run:
# library(vlad)
# patient Cusum values with different odds ratios, see Rigdon and Fricker p. 225, 226
coeff <- c("(Intercept)" = -3.67, "Parsonnet" = 0.077)
wt1 <- round(llr_score(df = data.frame(19L, 0), coeff = coeff, R0 = 1, RA = 2), 4)
wt2 <- round(llr_score(df = data.frame(19L, 0), coeff = coeff, R0 = 1, RA = 1/2), 5)
all.equal(racusum_scores(wt1 = wt1, wt2 = wt2), list(s1 = 0, s1l = 0.05083))
library("dplyr")
library("tidyr")
library(ggplot2)
data("cardiacsurgery", package = "spcadjust")
## preprocess data to 30 day mortality and subset phase I (In-control)
SALL <- cardiacsurgery %>% rename(s = Parsonnet) %>%
mutate(y = ifelse(status == 1 & time <= 30, 1, 0),
phase = factor(ifelse(date < 2*365, "I", "II")))
## subset phase I (In-control)
SI <- filter(SALL, phase == "I") %>% select(s, y)
## estimate coefficients from logit model
coeff1 <- round(coef(glm(y ~ s, data = SI, family = "binomial")), 3)
## subset phase II of surgeons 2
S2II <- filter(SALL, phase == "II", surgeon == 2) %>% select(s, y)
n <- nrow(S2II)
## CUSUM statistic without reset
wt1 <- sapply(1:n, function(i) llr_score(S2II[i, c("s", "y")], coeff = coeff, RA = 2))
wt2 <- sapply(1:n, function(i) llr_score(S2II[i, c("s", "y")], coeff = coeff, RA = 1/2))
cv <- racusum_scores(wt1 = wt1, wt2 = wt2)
s1 <- cv$s1; s1l <- cv$s1l
dm1 <- data.frame(cbind("n" = 1:length(s1), "Cup" = s1, "Clow" = -s1l, "h1" = 2, "h2" = -2))
## CUSUM statistic reset after signal
cv <- racusum_scores(wt1 = wt1, wt2 = wt2, reset = TRUE, h1 = 2, h2 = 2)
s1 <- cv$s1; s1l <- cv$s1l
dm2 <- data.frame(cbind("n" = 1:length(s1), "Cup" = s1, "Clow" = -s1l, "h1" = 2, "h2" = -2))
## plot
dm3 <- bind_rows(dm1, dm2, .id = "type")
dm3$type <- recode_factor(dm3$type, `1`="No resetting", `2`="Resetting")
dm3 %>%
gather("CUSUM", value, c(-n, - type)) %>%
ggplot(aes(x = n, y = value, colour = CUSUM, group = CUSUM)) +
geom_hline(yintercept = 0, colour = "darkgreen", linetype = "dashed") +
geom_line(size = 0.5) +
facet_wrap( ~ type, ncol = 1, scales = "free") +
labs(x = "Patient number n", y = "CUSUM values") + theme_classic() +
scale_y_continuous(sec.axis = dup_axis(name = NULL, labels = NULL)) +
scale_x_continuous(sec.axis = dup_axis(name = NULL, labels = NULL)) +
guides(colour = "none") +
scale_color_manual(values = c("blue", "orange", "red", "red"))
## End(Not run)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.