Nothing
#' @export
SeqAllocplot <-
function(mysim,bporder=NULL,stratum=F,cexsize=0.7) {
numschemes = length(mysim$schemes)
if (is.null(bporder) ) bporder = 1:numschemes
if (stratum==T) {
bporder = bporder[substr(mysim$schemes[bporder],1,1)!="P"]
}
deslabel = mysim$schemes
cguesslim = c(min(mysim$perccorr,mysim$perccorr_strat),max(mysim$perccorr,mysim$perccorr_strat))
cguess90lim = cguesslim
cguess90lim[1] = min(c(50,mysim$perccorr[6,]))
MAIClim = c(0,max(mysim$MAIC))
Rsquared = 100*mysim$Rsquared
R2lim = c(0,max(Rsquared))
# Plot CG, imbalance
old.par <- par(no.readonly = TRUE) # current par settings, to restore at end
par(pty="s",ask=T)
boxplot(mysim$perccorr[c(1,2,3,4,5,8),bporder] ,names=deslabel[bporder],range=0,ylim=cguesslim,
ylab="Percent Guessed Correctly (CG)",xlab="Randomization Design",cex.axis=cexsize)
boxplot(mysim$perccorr_strat[c(1,2,3,4,5,8),bporder] ,names=deslabel[bporder],range=0,ylim=cguesslim,
ylab="Percent Guessed Correctly by Stratum (CGs)",xlab="Randomization Design",cex.axis=cexsize)
boxplot(Rsquared[c(1,2,3,4,5,8),bporder] ,names=deslabel[bporder],range=0,ylim=R2lim,
ylab="R Squared (percent)",xlab="Randomization Design",cex.axis=cexsize)
boxplot(mysim$MAIC[c(1,2,3,4,5,8),bporder] ,names=deslabel[bporder],range=0,ylim=MAIClim,
ylab="Maximum Covariate Imbalance (MAIC)",xlab="Randomization Design",cex.axis=cexsize)
boxplot(mysim$WAIC[c(1,2,3,4,5,8),bporder] ,names=deslabel[bporder],range=0,ylim=MAIClim,
ylab="Weighted Average Covariate Imbalance (WAIC)",xlab="Randomization Design",cex.axis=cexsize)
boxplot(mysim$AI[c(1,2,3,4,5,8),bporder] ,names=deslabel[bporder],range=0,
ylab="Imbalance in Treatment Allocation (AI)",xlab="Randomization Design",cex.axis=cexsize)
plot(mysim$AI[8,bporder],mysim$perccorr[8,bporder],type="n",
xlab="Maximum Imbalance in Treatment Allocation (AI)",
ylab="Maximum Percent of Assignments Guessed Correctly (CG)",
ylim=cguess90lim)
text(mysim$AI[8,bporder],mysim$perccorr[8,bporder],labels=deslabel[bporder],cex=cexsize)
box()
plot(mysim$AI[6,bporder],mysim$perccorr[6,bporder],type="n",
xlab="90th Percentile of Imbalance in Treatment Allocation (AI)",
ylab="90th Percentile of Percent of Assignments Guessed Correctly (CG)",
ylim=cguess90lim)
text(mysim$AI[6,bporder],mysim$perccorr[6,bporder],labels=deslabel[bporder],cex=cexsize)
box()
plot(mysim$AI[8,bporder],mysim$perccorr_strat[8,bporder],type="n",
xlab="Maximum Imbalance in Treatment Allocation (AI)",
ylab="Maximum Percent of Assignments Guessed Correctly by Stratum (CGs)",
ylim=cguess90lim)
text(mysim$AI[8,bporder],mysim$perccorr_strat[8,bporder],labels=deslabel[bporder],cex=cexsize)
box()
plot(mysim$AI[6,bporder],mysim$perccorr_strat[6,bporder],type="n",
xlab="90th Percentile of Imbalance in Treatment Allocation (AI)",
ylab="90th Percentile of Percent of Assignments Guessed Correctly by Stratum (CGs)",
ylim=cguess90lim)
text(mysim$AI[6,bporder],mysim$perccorr[6,bporder],labels=deslabel[bporder],cex=cexsize)
box()
plot(Rsquared[8,bporder],mysim$perccorr_strat[8,bporder],type="n",
xlab="Maximum of Rsquared (percent)",
ylab="Maximum Percent of Assignments Guessed Correctly by Stratum (CGs)",
xlim = R2lim, ylim=cguess90lim)
text(Rsquared[8,bporder],mysim$perccorr_strat[8,bporder],labels=deslabel[bporder],cex=cexsize)
box()
plot(Rsquared[6,bporder],mysim$perccorr_strat[6,bporder],type="n",
xlab="90th Percentile of Rsquared (percent)",
ylab="90th Percentile, Assignments Guessed Correctly by Stratum (CGs)",
xlim = c(0,max(Rsquared[6,bporder])), ylim=cguess90lim)
text(Rsquared[6,bporder],mysim$perccorr_strat[6,bporder],labels=deslabel[bporder],cex=cexsize)
box()
plot(mysim$WAIC[8,bporder],mysim$perccorr_strat[8,bporder],type="n",
xlab="Maximum of Weighted Avg Covariate Imbalance (WAIC)",
ylab="Maximum Percent of Assignments Guessed Correctly by Stratum (CGs)",
xlim = MAIClim, ylim=cguess90lim)
text(mysim$WAIC[8,bporder],mysim$perccorr_strat[8,bporder],labels=deslabel[bporder],cex=cexsize)
box()
plot(mysim$WAIC[6,bporder],mysim$perccorr_strat[6,bporder],type="n",
xlab="90th Percentile of Weighted Avg Covariate Imbalance (WAIC)",
ylab="90th Percentile, Assignments Guessed Correctly by Stratum (CGs)",
xlim = c(0,max(mysim$WAIC[6,bporder])), ylim=cguess90lim)
text(mysim$WAIC[6,bporder],mysim$perccorr_strat[6,bporder],labels=deslabel[bporder],cex=cexsize)
box()
plot(mysim$MAIC[8,bporder],mysim$perccorr_strat[8,bporder],type="n",
xlab="Maximum of Maximum Covariate Imbalance (MAIC)",
ylab="Maximum Percent of Assignments Guessed Correctly by Stratum (CGs)",
xlim = MAIClim, ylim=cguess90lim)
text(mysim$MAIC[8,bporder],mysim$perccorr_strat[8,bporder],labels=deslabel[bporder],cex=cexsize)
box()
plot(mysim$WAIC[6,bporder],mysim$perccorr_strat[6,bporder],type="n",
xlab="90th Percentile of Maximum Covariate Imbalance (MAIC)",
ylab="90th Percentile, Assignments Guessed Correctly by Stratum (CGs)",
xlim = MAIClim, ylim=cguess90lim)
text(mysim$MAIC[6,bporder],mysim$perccorr_strat[6,bporder],labels=deslabel[bporder],cex=cexsize)
box()
par(old.par)
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.