dat <- read.csv('//cdsnas/oebdbdms/Graphics/Datasets/CleanTrial.csv')
base <- subset(dat, visit==2)
eot <- subset(dat, visit==6)
    eot$binep <- ifelse(base$catvar-eot$catvar >= 2, 1, 0)
    # Suppose this actually is from two studies
    eot$study <- rep(c('Study 1','Study 2', 'Study 1', 'Study 2'),
                     c(450,300,450,300))
                        
ss <- with(eot, summarize(100*binep, llist(racef, study, trtf), 
                              smean.cl.normal))

    ss$xaxis <- rep(1:4, each=4)+rep(c(-.1,.1), 8)
    names(ss)[4] <- 'binep'

# Calculate counts and sample sizes for the table
a1 <- with(eot[eot$study%in%'Study 1',], ftable(trtf, racef, binep))
    xs1 <- a1[,2]
    n1 <- a1[,1]+a1[,2]

a2 <- with(eot[eot$study%in%'Study 2',], ftable(trtf, racef, binep))
    xs2 <- a2[,2]
    n2 <- a2[,1]+a2[,2]

xpos <- c(.85,1.85,2.85,3.85,1.15,2.15,3.15,4.15)
cols <- rep(c('black','seagreen2'),each=4)

#png('C:/Research/Graphics/Graphs4Display/webpages/classes/pages/images/plottable.png',
#         width=700, height=700)

new.line <- trellis.par.get('superpose.line')
new.line$col <- c('black','seagreen2')
new.line$lty <- c(1,1,1,1)
new.symbol <- trellis.par.get('superpose.symbol')
new.symbol$col <- c('black', 'seagreen2')
new.symbol$pch <- c(1, 4, 16, 8)
trellis.par.set('superpose.line', new.line)
trellis.par.set('superpose.symbol', new.symbol)
        
xYplot(Cbind(binep,Lower,Upper)~xaxis|study, groups=trtf, data=ss,
       xlab='Race',
       ylab='Percent Responders',
       ylim=c(ss$Lower-15,ss$Upper+1),
       aspect=1,
       scales=list(x=list(at=1:4, labels=(unique(ss$racef))),
                   y=list(at=seq(20,60,10), labels=as.character(seq(20,60,10)))),
       key=list(type='p',
          points=list(pch=trellis.par.get('superpose.symbol')$pch[1:2],
                      col=trellis.par.get('superpose.symbol')$col[1:2]),
          text=list(levels(base$trtf),
                      col=trellis.par.get('superpose.symbol')$col[1:2]),
          columns=2, cex=1.25, title='Treatment'))
 
# Overall means of the study
    oo <- with(eot, summarize(100*binep, llist(study,trtf), mean))

trellis.focus('panel',1,1, highlight=FALSE)
panel.abline(h=oo[1:2,3], col=trellis.par.get('superpose.symbol')$col[1:2], lty=c(2,2))
for(i in 1:8){
    ltext(x=xpos[i], y=8, labels=bquote(frac(.(xs1[i]),.(n1[i]))),
           cex=.95, col=cols[i])
}
panel.abline(h=14, col='grey60')
trellis.unfocus()
             
trellis.focus('panel',2,1, highlight=FALSE)
panel.abline(h=oo[3:4,3], col=trellis.par.get('superpose.symbol')$col[1:2], lty=c(2,2))
for(i in 1:8){
    ltext(x=xpos[i], y=8, labels=bquote(frac(.(xs2[i]),.(n2[i]))),
        cex=.95, col=cols[i])
}             
panel.abline(h=14, col='grey60')
trellis.unfocus()

t1 <- with(eot[eot$study%in%'Study 1',], table(trtf))
t2 <- with(eot[eot$study%in%'Study 2',], table(trtf))

trellis.focus('strip', 1, 1, highlight=FALSE)
ltext(x=0.025, y=.5, paste('N=', t1[1], sep=''), 
      col=c('black'), adj=c(0,NA), cex=.9)
ltext(x=0.975, y=.5, paste('N=', t1[2], sep=''), 
      col=c('seagreen2'), adj=c(1,NA), cex=.9)
trellis.unfocus()
trellis.focus('strip', 2, 1, highlight=FALSE)
ltext(x=0.025, y=.5, paste('N=', t2[1], sep=''), 
      col=c('black'), adj=c(0,NA), cex=.9)
ltext(x=0.975, y=.5, paste('N=', t2[2], sep=''), 
      col=c('seagreen2'), adj=c(1,NA), cex=.9)
trellis.unfocus()
#dev.off()