In n8thangreen/IDEAdectree: The IDEA study clinical data health economics analysis with decision trees
knitr::opts_chunk$set(
fig.path = "MAINCHAPTER-QFN_TSPOT_files/"
)
# source("../../../analysis scripts/IDEA/alt-YAML_Binomial_dectrees/indiv-dectree-sampling.R")
library(IDEAdectree)
library(BCEA)
library(ggplot2)
# load("C:/Users/ngreen1/Dropbox/TB/IDEA/R/packages/IDEAdectree/data/TBdata_clinical_cleaned.RData")
load("../data/TBdata_clinical_cleaned.RData")
load("../data/COSTdistns_allerror.RData")
load("../data/senspec_env.RData")
load("../data/drug_dose-cost.RData")
## sensitivities and specificities from IDEA lab data
attach(senspec.env)
dat <- list()
yearindays <- 365.25
WTP <- c(20000, 30000)/yearindays
##TODO##
## doesnt work at the moment...!!
# dat1 <- IDEAdectree.simple(data=data, name.ruleout = "TSPOT",
# SPEC = TSPOT.noIndet.spec.mean, SENS = TSPOT.noIndet.sens.mean,
# SPECvar = TSPOT.noIndet.spec.var, SENSvar = TSPOT.noIndet.sens.var, wholecohortstats = TRUE)
# dat2 <- IDEAdectree.simple(data=data, name.ruleout = "TSPOT",
# SPEC = TSPOT.HIV.noIndet.spec.mean, SENS = TSPOT.HIV.noIndet.sens.mean,
# SPECvar = TSPOT.HIV.noIndet.spec.var, SENSvar = TSPOT.HIV.noIndet.sens.var, wholecohortstats = TRUE)
# dat3 <- IDEAdectree.simple(data=data, name.ruleout = "TSPOT",
# SPEC = TSPOT.HIVneg.noIndet.spec.mean, SENS = TSPOT.HIVneg.noIndet.sens.mean,
# SPECvar = TSPOT.HIVneg.noIndet.spec.var, SENSvar = TSPOT.HIVneg.noIndet.sens.var, wholecohortstats = TRUE)
#
# dat$e <- cbind(dat1$e, dat2$e[,2], dat3$e[,2])
# dat$c <- cbind(dat1$c, dat2$c[,2], dat3$c[,2])
#
# intlabels <- c("Current",
# "Enhanced TSPOT: All, no Indets", "Enhanced TSPOT: HIV positive, no Indets", "Enhanced TSPOT: HIV negative, no Indets")
#
# my.plot.bcea(dat1, dat2, dat3, wtp=WTP, intlabels = intlabels, wtpNEG = "Y")
# my.plot.bcea(dat1, dat2, dat3, wtp=WTP*yearindays, intlabels = c("All","HIV positive","HIV negative"), wtpNEG = "Y", SCALEcosts=FALSE, SCALEdays=FALSE, labelLong=FALSE, TITLE="(a)", N=769)
#
# my.plot.bcea(dat1, dat2, dat3, wtp=WTP, intlabels = intlabels, contour=TRUE, wtpNEG = "Y")
# my.plot.bcea(dat1, dat2, dat3, wtp=WTP*yearindays, intlabels = c("All","HIV positive","HIV negative"), contour=TRUE, wtpNEG = "Y", SCALEcosts=FALSE, SCALEdays=FALSE, labelLong=FALSE, TITLE="(a)", N=769)
#
# my.plot.bcea(dat1, dat2, dat3, wtp=WTP, intlabels = intlabels, contour=TRUE, LEVELS=0.5, wtpNEG = "Y")
# my.plot.bcea(dat1, dat2, dat3, wtp=WTP*yearindays, intlabels = c("All","HIV positive","HIV negative"), contour=TRUE, LEVELS=0.5, wtpNEG = "Y", SCALEcosts=FALSE, SCALEdays=FALSE, labelLong=FALSE, TITLE="(a)", N=769)
#
# my.plot.ceac(dat1, dat2, dat3, intlabels = intlabels)
dat1 <- IDEAdectree.simple(data = data,
name.ruleout = "TSPOT",
SPEC = TSPOT.noIndet.spec.mean,
SENS = TSPOT.noIndet.sens.mean,
SPECvar = TSPOT.noIndet.spec.var,
SENSvar = TSPOT.noIndet.sens.var)
dat2 <- IDEAdectree.simple(data = data,
name.ruleout = "TSPOT",
SPEC = TSPOT.HIV.noIndet.spec.mean,
SENS = TSPOT.HIV.noIndet.sens.mean,
SPECvar = TSPOT.HIV.noIndet.spec.var,
SENSvar = TSPOT.HIV.noIndet.sens.var)
dat3 <- IDEAdectree.simple(data = data,
name.ruleout = "TSPOT",
SPEC = TSPOT.HIVneg.noIndet.spec.mean,
SENS = TSPOT.HIVneg.noIndet.sens.mean,
SPECvar = TSPOT.HIVneg.noIndet.spec.var,
SENSvar = TSPOT.HIVneg.noIndet.sens.var)
dat$e <- cbind(dat1$e, dat2$e[,2], dat3$e[,2])
dat$c <- cbind(dat1$c, dat2$c[,2], dat3$c[,2])
intlabels <- c("Current",
"Enhanced TSPOT: All, no Indets",
"Enhanced TSPOT: HIV positive, no Indets",
"Enhanced TSPOT: HIV negative, no Indets")
# m <- bcea(e=dat$e, c=-dat$c, ref=1, interventions = intlabels)
# contour2(m, wtp=WTP, graph = "ggplot2", ICER.size=2, pos=c(0.1,0.9))+#, xlim=c(-5,5), ylim=c(-200,200)) +
# ggtitle("") #+ geom_abline(intercept = 0, slope = WTP)
my.plot.bcea(dat1, dat2, dat3, wtp = WTP, intlabels = intlabels, wtpNEG = "Y")
my.plot.bcea(dat1, dat2, dat3,
wtp = WTP*yearindays,
intlabels = c("All", "HIV positive", "HIV negative"),
wtpNEG = "Y",
SCALEcosts = FALSE,
SCALEdays = FALSE,
labelLong = FALSE,
TITLE = "(a)",
N = 769)
my.plot.bcea(dat1, dat2, dat3,
wtp = WTP,
intlabels = intlabels,
contour = TRUE,
wtpNEG = "Y")
my.plot.bcea(dat1, dat2, dat3,
wtp = WTP*yearindays,
intlabels = c("All", "HIV positive","HIV negative"),
contour = TRUE,
wtpNEG = "Y",
SCALEcosts = FALSE,
SCALEdays = FALSE,
labelLong = FALSE,
TITLE = "(a)",
N = 769)
my.plot.bcea(dat1, dat2, dat3,
wtp = WTP,
intlabels = intlabels,
contour = TRUE,
LEVELS = 0.5,
wtpNEG = "Y")
my.plot.bcea(dat1, dat2, dat3,
wtp = WTP*yearindays,
intlabels = c("All", "HIV positive", "HIV negative"),
contour = TRUE,
LEVELS = 0.5,
wtpNEG = "Y",
SCALEcosts = FALSE,
SCALEdays = FALSE,
labelLong = FALSE,
TITLE = "(a)",
N = 769)
## CEAC
my.plot.ceac(dat1, dat2, dat3, intlabels = c("All","HIV positive","HIV negative"), labelLong = FALSE, TITLE = "(a)")
my.plot.ceac(dat1, dat2, dat3, intlabels = c("All","HIV positive","HIV negative"), labelLong = FALSE, TITLE = "(a)", SCALEcosts = FALSE, SCALEdays = FALSE, N = 769)
my.plot.ceac(dat1, dat2, dat3, intlabels = c("All","HIV positive","HIV negative"), labelLong = FALSE, TITLE = "(a)", SCALEcosts = FALSE, SCALEdays = FALSE, N = 769, CI = TRUE)
## in years (not days)
# m <- bcea(e=dat$e/365, c=-dat$c, ref=1, interventions = intlabels)
# contour2(m, wtp=20000, graph = "ggplot2", ICER.size=2, pos=c(0.1,0.9))
#
# ceac.plot(m)
dat1 <- IDEAdectree.simple(data = data,
name.ruleout = "TSPOT",
SPEC = TSPOT.Indet.spec.mean,
SENS = TSPOT.Indet.sens.mean,
SPECvar = TSPOT.Indet.spec.var,
SENSvar = TSPOT.Indet.sens.var)
dat2 <- IDEAdectree.simple(data=data, name.ruleout = "TSPOT",
SPEC = TSPOT.HIV.Indet.spec.mean, SENS = TSPOT.HIV.Indet.sens.mean,
SPECvar = TSPOT.HIV.Indet.spec.var, SENSvar = TSPOT.HIV.Indet.sens.var)
dat3 <- IDEAdectree.simple(data=data, name.ruleout = "TSPOT",
SPEC = TSPOT.HIVneg.Indet.spec.mean, SENS = TSPOT.HIVneg.Indet.sens.mean,
SPECvar = TSPOT.HIVneg.Indet.spec.var, SENSvar = TSPOT.HIVneg.Indet.sens.var)
dat$e <- cbind(dat1$e, dat2$e[,2], dat3$e[,2])
dat$c <- cbind(dat1$c, dat2$c[,2], dat3$c[,2])
intlabels <- c("Current", "Enhanced TSPOT: All, with Indets", "Enhanced TSPOT: HIV positive, with Indets", "Enhanced TSPOT: HIV negative, with Indets")
# m <- bcea(e=dat$e, c=-dat$c, ref=1, interventions = intlabels)
# contour2(m, wtp=WTP, graph = "ggplot2", ICER.size=2, pos=c(0.1,0.9))+#, xlim=c(-5,5), ylim=c(-200,200)) +
# ggtitle("") #+ geom_abline(intercept = 0, slope = WTP)
my.plot.bcea(dat1, dat2, dat3, wtp=WTP, intlabels = intlabels, wtpNEG = "Y")
my.plot.bcea(dat1, dat2, dat3, wtp=WTP*yearindays, intlabels = c("All","HIV positive","HIV negative"), wtpNEG = "Y", SCALEcosts=FALSE, SCALEdays=FALSE, labelLong=FALSE, TITLE="(b)", N=769)
my.plot.bcea(dat1, dat2, dat3, wtp=WTP, intlabels = intlabels, contour=TRUE, wtpNEG = "Y")
my.plot.bcea(dat1, dat2, dat3, wtp=WTP*yearindays, intlabels = c("All","HIV positive","HIV negative"), contour=TRUE, wtpNEG = "Y", SCALEcosts=FALSE, SCALEdays=FALSE, labelLong=FALSE, TITLE="(b)", N=769)
my.plot.bcea(dat1, dat2, dat3, wtp=WTP, intlabels = intlabels, contour=TRUE, LEVELS=0.5, wtpNEG = "Y")
my.plot.bcea(dat1, dat2, dat3, wtp=WTP*yearindays, intlabels = c("All","HIV positive","HIV negative"), contour=TRUE, LEVELS=0.5, wtpNEG = "Y", SCALEcosts=FALSE, SCALEdays=FALSE, labelLong=FALSE, TITLE="(b)", N=769)
my.plot.ceac(dat1, dat2, dat3, intlabels = c("All","HIV positive","HIV negative"), labelLong=FALSE, TITLE="(b)")
my.plot.ceac(dat1, dat2, dat3, intlabels = c("All","HIV positive","HIV negative"), labelLong=FALSE, TITLE="(b)", SCALEcosts=FALSE, SCALEdays=FALSE, N=769)
my.plot.ceac(dat1, dat2, dat3, intlabels = c("All","HIV positive","HIV negative"), labelLong=FALSE, TITLE="(b)", SCALEcosts=FALSE, SCALEdays=FALSE, N=769, CI=TRUE)
## in years (not days)
# m <- bcea(e=dat$e/365, c=-dat$c, ref=1, interventions = intlabels)
# contour2(m, wtp=20000, graph = "ggplot2", ICER.size=2, pos=c(0.1,0.9))
#
# ceac.plot(m)
dat1 <- IDEAdectree.simple(data=data, name.ruleout = "QFN",
SPEC = QFN.noIndet.spec.mean, SENS = QFN.noIndet.sens.mean,
SPECvar = QFN.noIndet.spec.var, SENSvar = QFN.noIndet.sens.var)
dat2 <- IDEAdectree.simple(data=data, name.ruleout = "QFN",
SPEC = QFN.HIV.noIndet.spec.mean, SENS = QFN.HIV.noIndet.sens.mean,
SPECvar = QFN.HIV.noIndet.spec.var, SENSvar = QFN.HIV.noIndet.sens.var)
dat3 <- IDEAdectree.simple(data=data, name.ruleout = "QFN",
SPEC = QFN.HIVneg.noIndet.spec.mean, SENS = QFN.HIVneg.noIndet.sens.mean,
SPECvar = QFN.HIVneg.noIndet.spec.var, SENSvar = QFN.HIVneg.noIndet.sens.var)
dat$e <- cbind(dat1$e, dat2$e[,2], dat3$e[,2])
dat$c <- cbind(dat1$c, dat2$c[,2], dat3$c[,2])
intlabels <- c("Current",
"Enhanced QFN: All, no Indets", "Enhanced QFN: HIV positive, no Indets", "Enhanced QFN: HIV negative, no Indets")
# m <- bcea(e=dat$e, c=-dat$c, ref=1, interventions = intlabels)
# contour2(m, wtp=WTP, graph = "ggplot2", ICER.size=2, pos=c(0.1,0.9))+#, xlim=c(-5,5), ylim=c(-200,200)) +
# ggtitle("") #+ geom_abline(intercept = 0, slope = WTP)
my.plot.bcea(dat1, dat2, dat3, wtp=WTP, intlabels = intlabels, wtpNEG = "Y")
my.plot.bcea(dat1, dat2, dat3, wtp=WTP*yearindays, intlabels = c("All","HIV positive","HIV negative"), wtpNEG = "Y", SCALEcosts=FALSE, SCALEdays=FALSE, labelLong=FALSE, TITLE="(c)", N=769)
my.plot.bcea(dat1, dat2, dat3, wtp=WTP, intlabels = intlabels, contour=TRUE, wtpNEG = "Y")
my.plot.bcea(dat1, dat2, dat3, wtp=WTP*yearindays, intlabels = c("All","HIV positive","HIV negative"), contour=TRUE, wtpNEG = "Y", SCALEcosts=FALSE, SCALEdays=FALSE, labelLong=FALSE, TITLE="(c)", N=769)
my.plot.bcea(dat1, dat2, dat3, wtp=WTP, intlabels = intlabels, contour=TRUE, LEVELS=0.5, wtpNEG = "Y")
my.plot.bcea(dat1, dat2, dat3, wtp=WTP*yearindays, intlabels = c("All","HIV positive","HIV negative"), contour=TRUE, LEVELS=0.5, wtpNEG = "Y", SCALEcosts=FALSE, SCALEdays=FALSE, labelLong=FALSE, TITLE="(c)", N=769)
my.plot.ceac(dat1, dat2, dat3, intlabels = c("All","HIV positive","HIV negative"), labelLong=FALSE, TITLE="(c)")
my.plot.ceac(dat1, dat2, dat3, intlabels = c("All","HIV positive","HIV negative"), labelLong=FALSE, TITLE="(c)", SCALEcosts=FALSE, SCALEdays=FALSE, N=769)
my.plot.ceac(dat1, dat2, dat3, intlabels = c("All","HIV positive","HIV negative"), labelLong=FALSE, TITLE="(c)", SCALEcosts=FALSE, SCALEdays=FALSE, N=769, CI=TRUE)
## in years (not days)
# m <- bcea(e=dat$e/365, c=-dat$c, ref=1, interventions = intlabels)
# contour2(m, wtp=20000, graph = "ggplot2", ICER.size=2, pos=c(0.1,0.9))
#
# ceac.plot(m)
dat1 <- IDEAdectree.simple(data=data, name.ruleout = "QFN",
SPEC = QFN.Indet.spec.mean, SENS = QFN.Indet.sens.mean,
SPECvar = QFN.Indet.spec.var, SENSvar = QFN.Indet.sens.var)
dat2 <- IDEAdectree.simple(data=data, name.ruleout = "QFN",
SPEC = QFN.HIV.Indet.spec.mean, SENS = QFN.HIV.Indet.sens.mean,
SPECvar = QFN.HIV.Indet.spec.var, SENSvar = QFN.HIV.Indet.sens.var)
dat3 <- IDEAdectree.simple(data=data, name.ruleout = "QFN",
SPEC = QFN.HIVneg.Indet.spec.mean, SENS = QFN.HIVneg.Indet.sens.mean,
SPECvar = QFN.HIVneg.Indet.spec.var, SENSvar = QFN.HIVneg.Indet.sens.var)
dat$e <- cbind(dat1$e, dat2$e[,2], dat3$e[,2])
dat$c <- cbind(dat1$c, dat2$c[,2], dat3$c[,2])
intlabels <- c("Current", "Enhanced QFN: All, with Indets", "Enhanced QFN: HIV positive, with Indets", "Enhanced QFN: HIV negative, with Indets")
# m <- bcea(e=dat$e, c=-dat$c, ref=1, interventions = intlabels)
# contour2(m, wtp=WTP, graph = "ggplot2", ICER.size=2, pos=c(0.1,0.9))+#, xlim=c(-5,5), ylim=c(-200,200)) +
# ggtitle("") #+ geom_abline(intercept = 0, slope = WTP)
my.plot.bcea(dat1, dat2, dat3, wtp=WTP, intlabels = intlabels, wtpNEG = "Y")
my.plot.bcea(dat1, dat2, dat3, wtp=WTP*yearindays, intlabels = c("All","HIV positive","HIV negative"), wtpNEG = "Y", SCALEcosts=FALSE, SCALEdays=FALSE, labelLong=FALSE, TITLE="(d)", N=769)
my.plot.bcea(dat1, dat2, dat3, wtp=WTP, intlabels = intlabels, contour=TRUE, wtpNEG = "Y")
my.plot.bcea(dat1, dat2, dat3, wtp=WTP*yearindays, intlabels = c("All","HIV positive","HIV negative"), contour=TRUE, wtpNEG = "Y", SCALEcosts=FALSE, SCALEdays=FALSE, labelLong=FALSE, TITLE="(d)", N=769)
my.plot.bcea(dat1, dat2, dat3, wtp=WTP, intlabels = intlabels, contour=TRUE, LEVELS=0.5, wtpNEG = "Y")
my.plot.bcea(dat1, dat2, dat3, wtp=WTP*yearindays, intlabels = c("All","HIV positive","HIV negative"), contour=TRUE, LEVELS=0.5, wtpNEG = "Y", SCALEcosts=FALSE, SCALEdays=FALSE, labelLong=FALSE, TITLE="(d)", N=769)
my.plot.ceac(dat1, dat2, dat3, intlabels = c("All","HIV positive","HIV negative"), labelLong=FALSE, TITLE="(d)")
my.plot.ceac(dat1, dat2, dat3, intlabels = c("All","HIV positive","HIV negative"), labelLong=FALSE, TITLE="(d)", SCALEcosts=FALSE, SCALEdays=FALSE, N=769)
my.plot.ceac(dat1, dat2, dat3, intlabels = c("All","HIV positive","HIV negative"), labelLong=FALSE, TITLE="(d)", SCALEcosts=FALSE, SCALEdays=FALSE, N=769, CI=TRUE)
## in years (not days)
# m <- bcea(e=dat$e/365, c=-dat$c, ref=1, interventions = intlabels)
# contour2(m, wtp=20000, graph = "ggplot2", ICER.size=2, pos=c(0.1,0.9))
#
# ceac.plot(m)
detach(senspec.env)
n8thangreen/IDEAdectree documentation built on Feb. 10, 2020, 11:35 a.m.
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knitr::opts_chunk$set( fig.path = "MAINCHAPTER-QFN_TSPOT_files/" )
# source("../../../analysis scripts/IDEA/alt-YAML_Binomial_dectrees/indiv-dectree-sampling.R")
library(IDEAdectree) library(BCEA) library(ggplot2) # load("C:/Users/ngreen1/Dropbox/TB/IDEA/R/packages/IDEAdectree/data/TBdata_clinical_cleaned.RData") load("../data/TBdata_clinical_cleaned.RData") load("../data/COSTdistns_allerror.RData") load("../data/senspec_env.RData") load("../data/drug_dose-cost.RData") ## sensitivities and specificities from IDEA lab data attach(senspec.env) dat <- list() yearindays <- 365.25 WTP <- c(20000, 30000)/yearindays
##TODO## ## doesnt work at the moment...!! # dat1 <- IDEAdectree.simple(data=data, name.ruleout = "TSPOT", # SPEC = TSPOT.noIndet.spec.mean, SENS = TSPOT.noIndet.sens.mean, # SPECvar = TSPOT.noIndet.spec.var, SENSvar = TSPOT.noIndet.sens.var, wholecohortstats = TRUE) # dat2 <- IDEAdectree.simple(data=data, name.ruleout = "TSPOT", # SPEC = TSPOT.HIV.noIndet.spec.mean, SENS = TSPOT.HIV.noIndet.sens.mean, # SPECvar = TSPOT.HIV.noIndet.spec.var, SENSvar = TSPOT.HIV.noIndet.sens.var, wholecohortstats = TRUE) # dat3 <- IDEAdectree.simple(data=data, name.ruleout = "TSPOT", # SPEC = TSPOT.HIVneg.noIndet.spec.mean, SENS = TSPOT.HIVneg.noIndet.sens.mean, # SPECvar = TSPOT.HIVneg.noIndet.spec.var, SENSvar = TSPOT.HIVneg.noIndet.sens.var, wholecohortstats = TRUE) # # 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 TSPOT: All, no Indets", "Enhanced TSPOT: HIV positive, no Indets", "Enhanced TSPOT: HIV negative, no Indets") # # my.plot.bcea(dat1, dat2, dat3, wtp=WTP, intlabels = intlabels, wtpNEG = "Y") # my.plot.bcea(dat1, dat2, dat3, wtp=WTP*yearindays, intlabels = c("All","HIV positive","HIV negative"), wtpNEG = "Y", SCALEcosts=FALSE, SCALEdays=FALSE, labelLong=FALSE, TITLE="(a)", N=769) # # my.plot.bcea(dat1, dat2, dat3, wtp=WTP, intlabels = intlabels, contour=TRUE, wtpNEG = "Y") # my.plot.bcea(dat1, dat2, dat3, wtp=WTP*yearindays, intlabels = c("All","HIV positive","HIV negative"), contour=TRUE, wtpNEG = "Y", SCALEcosts=FALSE, SCALEdays=FALSE, labelLong=FALSE, TITLE="(a)", N=769) # # my.plot.bcea(dat1, dat2, dat3, wtp=WTP, intlabels = intlabels, contour=TRUE, LEVELS=0.5, wtpNEG = "Y") # my.plot.bcea(dat1, dat2, dat3, wtp=WTP*yearindays, intlabels = c("All","HIV positive","HIV negative"), contour=TRUE, LEVELS=0.5, wtpNEG = "Y", SCALEcosts=FALSE, SCALEdays=FALSE, labelLong=FALSE, TITLE="(a)", N=769) # # my.plot.ceac(dat1, dat2, dat3, intlabels = intlabels)
dat1 <- IDEAdectree.simple(data = data, name.ruleout = "TSPOT", SPEC = TSPOT.noIndet.spec.mean, SENS = TSPOT.noIndet.sens.mean, SPECvar = TSPOT.noIndet.spec.var, SENSvar = TSPOT.noIndet.sens.var) dat2 <- IDEAdectree.simple(data = data, name.ruleout = "TSPOT", SPEC = TSPOT.HIV.noIndet.spec.mean, SENS = TSPOT.HIV.noIndet.sens.mean, SPECvar = TSPOT.HIV.noIndet.spec.var, SENSvar = TSPOT.HIV.noIndet.sens.var) dat3 <- IDEAdectree.simple(data = data, name.ruleout = "TSPOT", SPEC = TSPOT.HIVneg.noIndet.spec.mean, SENS = TSPOT.HIVneg.noIndet.sens.mean, SPECvar = TSPOT.HIVneg.noIndet.spec.var, SENSvar = TSPOT.HIVneg.noIndet.sens.var) 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 TSPOT: All, no Indets", "Enhanced TSPOT: HIV positive, no Indets", "Enhanced TSPOT: HIV negative, no Indets") # m <- bcea(e=dat$e, c=-dat$c, ref=1, interventions = intlabels) # contour2(m, wtp=WTP, graph = "ggplot2", ICER.size=2, pos=c(0.1,0.9))+#, xlim=c(-5,5), ylim=c(-200,200)) + # ggtitle("") #+ geom_abline(intercept = 0, slope = WTP) my.plot.bcea(dat1, dat2, dat3, wtp = WTP, intlabels = intlabels, wtpNEG = "Y") my.plot.bcea(dat1, dat2, dat3, wtp = WTP*yearindays, intlabels = c("All", "HIV positive", "HIV negative"), wtpNEG = "Y", SCALEcosts = FALSE, SCALEdays = FALSE, labelLong = FALSE, TITLE = "(a)", N = 769) my.plot.bcea(dat1, dat2, dat3, wtp = WTP, intlabels = intlabels, contour = TRUE, wtpNEG = "Y") my.plot.bcea(dat1, dat2, dat3, wtp = WTP*yearindays, intlabels = c("All", "HIV positive","HIV negative"), contour = TRUE, wtpNEG = "Y", SCALEcosts = FALSE, SCALEdays = FALSE, labelLong = FALSE, TITLE = "(a)", N = 769) my.plot.bcea(dat1, dat2, dat3, wtp = WTP, intlabels = intlabels, contour = TRUE, LEVELS = 0.5, wtpNEG = "Y") my.plot.bcea(dat1, dat2, dat3, wtp = WTP*yearindays, intlabels = c("All", "HIV positive", "HIV negative"), contour = TRUE, LEVELS = 0.5, wtpNEG = "Y", SCALEcosts = FALSE, SCALEdays = FALSE, labelLong = FALSE, TITLE = "(a)", N = 769) ## CEAC my.plot.ceac(dat1, dat2, dat3, intlabels = c("All","HIV positive","HIV negative"), labelLong = FALSE, TITLE = "(a)") my.plot.ceac(dat1, dat2, dat3, intlabels = c("All","HIV positive","HIV negative"), labelLong = FALSE, TITLE = "(a)", SCALEcosts = FALSE, SCALEdays = FALSE, N = 769) my.plot.ceac(dat1, dat2, dat3, intlabels = c("All","HIV positive","HIV negative"), labelLong = FALSE, TITLE = "(a)", SCALEcosts = FALSE, SCALEdays = FALSE, N = 769, CI = TRUE) ## in years (not days) # m <- bcea(e=dat$e/365, c=-dat$c, ref=1, interventions = intlabels) # contour2(m, wtp=20000, graph = "ggplot2", ICER.size=2, pos=c(0.1,0.9)) # # ceac.plot(m)
dat1 <- IDEAdectree.simple(data = data, name.ruleout = "TSPOT", SPEC = TSPOT.Indet.spec.mean, SENS = TSPOT.Indet.sens.mean, SPECvar = TSPOT.Indet.spec.var, SENSvar = TSPOT.Indet.sens.var) dat2 <- IDEAdectree.simple(data=data, name.ruleout = "TSPOT", SPEC = TSPOT.HIV.Indet.spec.mean, SENS = TSPOT.HIV.Indet.sens.mean, SPECvar = TSPOT.HIV.Indet.spec.var, SENSvar = TSPOT.HIV.Indet.sens.var) dat3 <- IDEAdectree.simple(data=data, name.ruleout = "TSPOT", SPEC = TSPOT.HIVneg.Indet.spec.mean, SENS = TSPOT.HIVneg.Indet.sens.mean, SPECvar = TSPOT.HIVneg.Indet.spec.var, SENSvar = TSPOT.HIVneg.Indet.sens.var) 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 TSPOT: All, with Indets", "Enhanced TSPOT: HIV positive, with Indets", "Enhanced TSPOT: HIV negative, with Indets") # m <- bcea(e=dat$e, c=-dat$c, ref=1, interventions = intlabels) # contour2(m, wtp=WTP, graph = "ggplot2", ICER.size=2, pos=c(0.1,0.9))+#, xlim=c(-5,5), ylim=c(-200,200)) + # ggtitle("") #+ geom_abline(intercept = 0, slope = WTP) my.plot.bcea(dat1, dat2, dat3, wtp=WTP, intlabels = intlabels, wtpNEG = "Y") my.plot.bcea(dat1, dat2, dat3, wtp=WTP*yearindays, intlabels = c("All","HIV positive","HIV negative"), wtpNEG = "Y", SCALEcosts=FALSE, SCALEdays=FALSE, labelLong=FALSE, TITLE="(b)", N=769) my.plot.bcea(dat1, dat2, dat3, wtp=WTP, intlabels = intlabels, contour=TRUE, wtpNEG = "Y") my.plot.bcea(dat1, dat2, dat3, wtp=WTP*yearindays, intlabels = c("All","HIV positive","HIV negative"), contour=TRUE, wtpNEG = "Y", SCALEcosts=FALSE, SCALEdays=FALSE, labelLong=FALSE, TITLE="(b)", N=769) my.plot.bcea(dat1, dat2, dat3, wtp=WTP, intlabels = intlabels, contour=TRUE, LEVELS=0.5, wtpNEG = "Y") my.plot.bcea(dat1, dat2, dat3, wtp=WTP*yearindays, intlabels = c("All","HIV positive","HIV negative"), contour=TRUE, LEVELS=0.5, wtpNEG = "Y", SCALEcosts=FALSE, SCALEdays=FALSE, labelLong=FALSE, TITLE="(b)", N=769) my.plot.ceac(dat1, dat2, dat3, intlabels = c("All","HIV positive","HIV negative"), labelLong=FALSE, TITLE="(b)") my.plot.ceac(dat1, dat2, dat3, intlabels = c("All","HIV positive","HIV negative"), labelLong=FALSE, TITLE="(b)", SCALEcosts=FALSE, SCALEdays=FALSE, N=769) my.plot.ceac(dat1, dat2, dat3, intlabels = c("All","HIV positive","HIV negative"), labelLong=FALSE, TITLE="(b)", SCALEcosts=FALSE, SCALEdays=FALSE, N=769, CI=TRUE) ## in years (not days) # m <- bcea(e=dat$e/365, c=-dat$c, ref=1, interventions = intlabels) # contour2(m, wtp=20000, graph = "ggplot2", ICER.size=2, pos=c(0.1,0.9)) # # ceac.plot(m)
dat1 <- IDEAdectree.simple(data=data, name.ruleout = "QFN", SPEC = QFN.noIndet.spec.mean, SENS = QFN.noIndet.sens.mean, SPECvar = QFN.noIndet.spec.var, SENSvar = QFN.noIndet.sens.var) dat2 <- IDEAdectree.simple(data=data, name.ruleout = "QFN", SPEC = QFN.HIV.noIndet.spec.mean, SENS = QFN.HIV.noIndet.sens.mean, SPECvar = QFN.HIV.noIndet.spec.var, SENSvar = QFN.HIV.noIndet.sens.var) dat3 <- IDEAdectree.simple(data=data, name.ruleout = "QFN", SPEC = QFN.HIVneg.noIndet.spec.mean, SENS = QFN.HIVneg.noIndet.sens.mean, SPECvar = QFN.HIVneg.noIndet.spec.var, SENSvar = QFN.HIVneg.noIndet.sens.var) 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 QFN: All, no Indets", "Enhanced QFN: HIV positive, no Indets", "Enhanced QFN: HIV negative, no Indets") # m <- bcea(e=dat$e, c=-dat$c, ref=1, interventions = intlabels) # contour2(m, wtp=WTP, graph = "ggplot2", ICER.size=2, pos=c(0.1,0.9))+#, xlim=c(-5,5), ylim=c(-200,200)) + # ggtitle("") #+ geom_abline(intercept = 0, slope = WTP) my.plot.bcea(dat1, dat2, dat3, wtp=WTP, intlabels = intlabels, wtpNEG = "Y") my.plot.bcea(dat1, dat2, dat3, wtp=WTP*yearindays, intlabels = c("All","HIV positive","HIV negative"), wtpNEG = "Y", SCALEcosts=FALSE, SCALEdays=FALSE, labelLong=FALSE, TITLE="(c)", N=769) my.plot.bcea(dat1, dat2, dat3, wtp=WTP, intlabels = intlabels, contour=TRUE, wtpNEG = "Y") my.plot.bcea(dat1, dat2, dat3, wtp=WTP*yearindays, intlabels = c("All","HIV positive","HIV negative"), contour=TRUE, wtpNEG = "Y", SCALEcosts=FALSE, SCALEdays=FALSE, labelLong=FALSE, TITLE="(c)", N=769) my.plot.bcea(dat1, dat2, dat3, wtp=WTP, intlabels = intlabels, contour=TRUE, LEVELS=0.5, wtpNEG = "Y") my.plot.bcea(dat1, dat2, dat3, wtp=WTP*yearindays, intlabels = c("All","HIV positive","HIV negative"), contour=TRUE, LEVELS=0.5, wtpNEG = "Y", SCALEcosts=FALSE, SCALEdays=FALSE, labelLong=FALSE, TITLE="(c)", N=769) my.plot.ceac(dat1, dat2, dat3, intlabels = c("All","HIV positive","HIV negative"), labelLong=FALSE, TITLE="(c)") my.plot.ceac(dat1, dat2, dat3, intlabels = c("All","HIV positive","HIV negative"), labelLong=FALSE, TITLE="(c)", SCALEcosts=FALSE, SCALEdays=FALSE, N=769) my.plot.ceac(dat1, dat2, dat3, intlabels = c("All","HIV positive","HIV negative"), labelLong=FALSE, TITLE="(c)", SCALEcosts=FALSE, SCALEdays=FALSE, N=769, CI=TRUE) ## in years (not days) # m <- bcea(e=dat$e/365, c=-dat$c, ref=1, interventions = intlabels) # contour2(m, wtp=20000, graph = "ggplot2", ICER.size=2, pos=c(0.1,0.9)) # # ceac.plot(m)
dat1 <- IDEAdectree.simple(data=data, name.ruleout = "QFN", SPEC = QFN.Indet.spec.mean, SENS = QFN.Indet.sens.mean, SPECvar = QFN.Indet.spec.var, SENSvar = QFN.Indet.sens.var) dat2 <- IDEAdectree.simple(data=data, name.ruleout = "QFN", SPEC = QFN.HIV.Indet.spec.mean, SENS = QFN.HIV.Indet.sens.mean, SPECvar = QFN.HIV.Indet.spec.var, SENSvar = QFN.HIV.Indet.sens.var) dat3 <- IDEAdectree.simple(data=data, name.ruleout = "QFN", SPEC = QFN.HIVneg.Indet.spec.mean, SENS = QFN.HIVneg.Indet.sens.mean, SPECvar = QFN.HIVneg.Indet.spec.var, SENSvar = QFN.HIVneg.Indet.sens.var) 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 QFN: All, with Indets", "Enhanced QFN: HIV positive, with Indets", "Enhanced QFN: HIV negative, with Indets") # m <- bcea(e=dat$e, c=-dat$c, ref=1, interventions = intlabels) # contour2(m, wtp=WTP, graph = "ggplot2", ICER.size=2, pos=c(0.1,0.9))+#, xlim=c(-5,5), ylim=c(-200,200)) + # ggtitle("") #+ geom_abline(intercept = 0, slope = WTP) my.plot.bcea(dat1, dat2, dat3, wtp=WTP, intlabels = intlabels, wtpNEG = "Y") my.plot.bcea(dat1, dat2, dat3, wtp=WTP*yearindays, intlabels = c("All","HIV positive","HIV negative"), wtpNEG = "Y", SCALEcosts=FALSE, SCALEdays=FALSE, labelLong=FALSE, TITLE="(d)", N=769) my.plot.bcea(dat1, dat2, dat3, wtp=WTP, intlabels = intlabels, contour=TRUE, wtpNEG = "Y") my.plot.bcea(dat1, dat2, dat3, wtp=WTP*yearindays, intlabels = c("All","HIV positive","HIV negative"), contour=TRUE, wtpNEG = "Y", SCALEcosts=FALSE, SCALEdays=FALSE, labelLong=FALSE, TITLE="(d)", N=769) my.plot.bcea(dat1, dat2, dat3, wtp=WTP, intlabels = intlabels, contour=TRUE, LEVELS=0.5, wtpNEG = "Y") my.plot.bcea(dat1, dat2, dat3, wtp=WTP*yearindays, intlabels = c("All","HIV positive","HIV negative"), contour=TRUE, LEVELS=0.5, wtpNEG = "Y", SCALEcosts=FALSE, SCALEdays=FALSE, labelLong=FALSE, TITLE="(d)", N=769) my.plot.ceac(dat1, dat2, dat3, intlabels = c("All","HIV positive","HIV negative"), labelLong=FALSE, TITLE="(d)") my.plot.ceac(dat1, dat2, dat3, intlabels = c("All","HIV positive","HIV negative"), labelLong=FALSE, TITLE="(d)", SCALEcosts=FALSE, SCALEdays=FALSE, N=769) my.plot.ceac(dat1, dat2, dat3, intlabels = c("All","HIV positive","HIV negative"), labelLong=FALSE, TITLE="(d)", SCALEcosts=FALSE, SCALEdays=FALSE, N=769, CI=TRUE) ## in years (not days) # m <- bcea(e=dat$e/365, c=-dat$c, ref=1, interventions = intlabels) # contour2(m, wtp=20000, graph = "ggplot2", ICER.size=2, pos=c(0.1,0.9)) # # ceac.plot(m)
detach(senspec.env)
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