Nothing
diag.plot <- function(x, plots, subset, ...){
treat <- x$treat
#propScores <- x$ps
weights <- x$w
# if (!all(weights[,1]==1)){
# weights <- cbind(unw=rep(1,nrow(weights)),weights)
# propScores <- cbind(unw=rep(0.5,nrow(propScores)),propScores)
# }
n.tp <- length(x$desc)
n.var <- nrow(x$desc$unw$bal.tab$results)
whichVar <- pVal <- weighted <- varb <- NULL
if (plots == "optimize") {
longBal <- matrix(t(x$balance))
optDat <- data.frame(balance = longBal, iteration = rep(x$iters, each = n.tp-1), stopRule = names(x$desc)[-1])
if(is.null(subset))
subset <- 1:length(levels(as.factor(optDat$stopRule)))
pt1 <- xyplot(balance ~ iteration | stopRule, data = optDat,
ylab = "Balance measure", xlab = "Iteration",
scales = list(alternating = 1),
subset = as.factor(optDat$stopRule) %in% levels(as.factor(optDat$stopRule))[subset], ...)
}
if (plots == "es") { ## es plot
desc.unw <- x$desc$unw$bal.tab$results$wcor
desc.AAC <- x$desc[[2]]$bal.tab$results$wcor
hld <- c(desc.AAC, desc.unw)
weighted = as.factor(rep(rep(c("Weighted", "Unweighted"), each = n.var)))
whichVar = factor(rep(rep(1:n.var), 2))
esDat <- data.frame(effectSize = abs(hld),
weighted = weighted, whichVar = whichVar)
yMax <- min(3, max(esDat$effectSize, na.rm=TRUE)) + .05
pt1 <- xyplot(effectSize ~ weighted, groups=whichVar, data = esDat,
scales = list(alternating = 1),
ylim = c(-.05, yMax), type = "l", col = "lightblue",
#subset = subsetHold,
ylab = "Absolute Correlation", xlab = NULL,
panel = function(...){
panel.abline(h=c(.1), col="gray80")
panel.xyplot(...)
})
}
if(!(plots %in% c("optimize","es")))
stop("plots must be one of 'optimize' or 'es' \n")
return(pt1)
}
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