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library(clinDR)
### note change in random number generator and set.seed
### produced some changes with earlier versions of the
### plots
if(file.exists("./clinDR/inst/tests/extraGraphics/pdfoutput")){
pvar<-"./clinDR/inst/tests/extraGraphics/pdfoutput"
} else pvar<-NULL
if(file.exists(file.path(pvar,"output.plotB_new.pdf"))) file.rename(file.path(pvar,"output.plotB_new.pdf"),
file.path(pvar,"output.plotB_old.pdf"))
pdf(file=paste(file.path(pvar,"output.plotB_new.pdf")))
set.seed(12357)
data(metaData)
dat<-metaData[metaData$taid==6 & metaData$poptype==1,]
attach(dat)
msSat<-sum((dat$sampsize-1)*(dat$sd)^2)/(sum(dat$sampsize)-length(dat$sampsize))
fit<-fitEmax(rslt,dose,modType=3,count=sampsize,msSat=msSat)
prior<-emaxPrior.control(epmu=0,epsca=10,difTargetmu=0,difTargetsca=10,dTarget=80.0,
p50=3.75,sigmalow=0.01,sigmaup=20)
fitb<-fitEmaxB(rslt,dose,prior,modType=4,count=sampsize,msSat=msSat,
mcmc=mcmc.control(iter=20000))
parms<-coef(fitb)
sigsim<-sigma(fitb)
##### basic plot
outB<-plotB(rslt,dose,parms[,1:4],(sigsim)^2,count=sampsize,
ylab="Y",xat=c(0, 40, 80))
plot(outB)
plot(outB, xat=c(0, 40, 80))
plot(outB, log=TRUE)
plot(outB, log=TRUE, xat=c(0, 5, 40, 80))
##### resid plot
plot(outB,plotResid=TRUE,predict=FALSE)
plot(outB,plotResid=TRUE,predict=FALSE, log=TRUE)
##### test symbol plotting
symbol<-rep(2,length(dose))
symbol[1:floor(length(dose)/2)]<-1
outB<-plotB(rslt,dose,parms[,1:4],(sigsim)^2,count=sampsize,symbol=symbol,
ylab="Cholesterol")
plot(outB,symbolShape=8:9,symbolColor=c('red','blue'),
symbolLabel='TESTNAME')
plot(outB,symbolShape=8:9,symbolColor=c('red','blue'),
symbolLabel='TESTNAME', log=TRUE)
#### use medians and no prediction
plot(outB,symbolShape=8:9,symbolColor=c('red','blue'),
symbolLabel='TESTNAME',plotMed=TRUE,predict=FALSE)
plot(outB,symbolShape=8:9,symbolColor=c('red','blue'),
symbolLabel='TESTNAME',plotMed=TRUE,predict=FALSE, log=TRUE)
### residual plot
plot(outB,symbolShape=8:9,symbolColor=c('red','blue'),
symbolLabel='TESTNAME',plotResid=TRUE)
plot(outB,symbolShape=8:9,symbolColor=c('red','blue'),
symbolLabel='TESTNAME',plotResid=TRUE, log=TRUE)
##### test as responder variable (Note: with small sample sizes
##### create patient level data the predictive intervals and
##### points are discrete with big
##### jumps
ymeans<-predict(fitb,dose)$pred
ymeans<-rep(ymeans,sampsize)
yvec<-rnorm(length(ymeans),ymeans,sd)
dvec<-rep(dose,sampsize)
outBB<-plotB(yvec,dvec,parms[,1:4],(sigsim)^2,
ylab="Change in LDL", log=TRUE)
plot(outBB,log=TRUE)
outBB<-plotB(yvec,dvec,parms[,1:4],(sigsim)^2,
ylab="Change in LDL",binary='BinRes',BinResLev=-40,BinResDir='<')
plot(outBB,log=TRUE)
plot(outBB)
##### test active comparator
set.seed(12357)
nac<-10
msd<-median(sigsim)
yac<-rnorm(nac,mean(rslt),msd)
ac<-rnorm(nrow(parms),mean(yac),msd/sqrt(nac))
outac<-plotB(rslt,dose,parms[,1:4],(sigsim)^2,count=sampsize,
ylab="Change in LDL vs Active Comparator",activeControl=TRUE,yac=yac,ac=ac,
labac='Active',plotDif=TRUE)
plot(outac,labac='Active',xat=c(0,.25,.5,.75,1))
plot(outac,labac='Active', log=TRUE, xat=c(0,.1,.5,1))
symbol<-rep(2,length(dose))
symbol[1:floor(length(dose)/2)]<-1
outac<-plotB(rslt,dose,parms[,1:4],(sigsim)^2,count=sampsize,symbol=symbol,
symbolShape=9:10,symbolColor=c('red','blue'),symbolLabel='TRT GROUP',
ylab="LDL with Active Comparator",activeControl=TRUE,yac=yac,ac=ac,
labac='Prednisone',shapeac=8,colac='green',xat=c(0,.25,.5,.75,1))
plot(outac,xat=c(0,.25,.5,.75,1),
symbolShape=9:10,symbolColor=c('red','blue'),symbolLabel='TESTNAME',
ylab="LDL with Active Comparator",activeControl=TRUE,yac=yac,ac=ac,
labac='Prednisone',shapeac=8,colac='green')
#### with responder outcome
symvec<-rep(symbol,sampsize)
outac<-plotB(yvec,dvec,parms[,1:4],(sigsim)^2,
ylab="Change in LDL vs Active Comparator",
activeControl=TRUE,yac=yac,ac=ac,
binary='BinRes',BinResLev=-40,BinResDir = '<')
outac<-plotB(yvec,dvec,parms[,1:4],(sigsim)^2,symbol=symvec,
symbolShape=9:10,symbolColor=c('red','blue'),symbolLabel='TESTNAME',
ylab="Change in LDL vs Active Comparator",
activeControl=TRUE,yac=yac,ac=ac,
binary='BinRes',BinResLev=-40,shapeac=8,colac='orange')
outac<-plotB(yvec,dvec,parms[,1:4],(sigsim)^2,
ylab="Change in EDD vs Active Comparator",
activeControl=TRUE,yac=yac,ac=ac,
binary='BinRes',BinResLev=-40)
plot(outac,symbolShape=9:10,symbolColor=c('red','blue'),
xat=c(0, 40, 80))
dev.off()
detach(dat)
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