IDEAdectree.simple: IDEA Decision Tree Calculation

In n8thangreen/IDEAdectree: The IDEA study clinical data health economics analysis with decision trees

Description

This is a parred down version of the full model that is used in the paper. This is specifically for the HTA chapter. It probabilistically incorporates sampling variability (and standard pathway cost and time to diagnosis).

Usage

IDEAdectree.simple(data, nsim = 1000,
  costDistns = COST.distns.allerror, prevalence = 0.25, cutoff = 1,
  FNtime = 42, FNdist = TRUE, SENS = 0.9, SPEC = 0.9,
  SENSvar = 0.005, SPECvar = 0.005, c.ruleout = 100,
  name.ruleout = NA, quant = 0.5, utility = NA, N = nrow(data),
  wholecohortstats = FALSE)

Arguments

data	IDEA study data
nsim	Number of sample points. Default: 1000
costDistns	List of distribution names and parameter values for each test/procedure
prevalence	As a probability. Default: 0.25
cutoff	Clinical judgement threshold
FNtime	False negative follow-up time
FNdist	Should false negative time to follow-up distribution be used (logical)
SENS	Sensitivity Rule-out test
SPEC	Specificity Rule-out test
SENSvar	Sensitivity variance
SPECvar	Specificiaty variance
c.ruleout	Rule-out test unit cost
name.ruleout	Name of rule-out test to get at distribution
quant	Quantile value of time to diagnosis and costs
utility	QALY adjustment utility due to active TB
N	Number of patients. The number in the data is used as default.
wholecohortstats	Should the output stats be the total or per patient

Value

Health and cost realisations

Examples

library(bcea)
dat1 <- IDEAdectree.simple(data, cutoff = 0.4, specificity = 0.8)
dat2 <- IDEAdectree.simple(data, cutoff = 0.4, specificity = 0.9)
dat3 <- IDEAdectree.simple(data, cutoff = 0.4, specificity = 0.99)

dat$e <- cbind(dat1$e, dat2$e[,2], dat3$e[,2])
dat$c <- cbind(dat1$c, dat2$c[,2], dat3$c[,2])

intlabels <- c("Current", "Enhanced specificity=0.8", "Enhanced specificity=0.9", "Enhanced specificity=0.99")

m <- bcea(e=dat$e, c=dat$c, ref=1, interventions = intlabels)
contour2(m, wtp=WTP, graph = "ggplot2", ICER.size=2, pos=c(0.9,0.1), xlim=c(-5,20), ylim=c(-100,500)) + ggtitle("")
summary(m)

n8thangreen/IDEAdectree documentation built on Feb. 10, 2020, 11:35 a.m.