#' @title Plot the design-based operating characteristics conditioned across a range of effects.
#'
#' @description Condition all but two monitoring frequency parameters (wait, steps, affirm, lag, N) must have a single value.
#'
#' @param am SeqSGPV object
#' @param stat Any of: rejH0, cover, bias, stopInconclusive, stopNotROPE, stopNotROME, stopInconsistent. Use prefix lag.x when some outcomes were lagged/delayed.
#' @param wait Vector of possible wait times (W) before monitoring.
#' @param steps Vector of the number of observations (S) in between monitoring assessments.
#' @param affirm Vector of the number of observations required for affirming a stopping rule (A) in between raising an alert of stopping.
#' @param lag Vector of the number of delayed outcomes between enrolling a single observation and observing its outcome.
#' @param N Vector of maximum sample size. Can be set as Inf (indefinite).
#' @param xlim Optional limits for x-axis.
#' @param ylim Optional limits for y-axis.
#' @param addRegions Defaults to TRUE to add PRISM boundaries to plot.
#' @param addRegionLines Defaults to TRUE to add PRISM boundary lines to plot.
#' @param addMain Provides default title for figure. Defaults to TRUE.
#' @param addLegend Provides default legend for figure. Defaults to TRUE.
#' @param ablineH Add any set of horizontal reference lines.
#' @param ablineV Add any set of vertical reference lines.
#' @param setMargins Optional figure margins
#' @param ylab ylab
#' @param ... additional plot parameters
#'
#' @export
<- ( am, stat, wait, steps, affirm, , N, , , ,
addRegions=, addRegionLines=, addMain = ,
addLegend=, ablineH=,ablineV=, setMargins, xlab,ylab="", ){
amInputs <- am[1]]$inputs
# 1 or 2 arm trial
((amInputs$allocation)==1){
effectX <- "effect0"
(amInputs$effectScale=="identity" & (xlab)){
xlab <- "Theta"
} ((xlab)){
xlab <- "Effect"
}
} {
effectX <- "effect1"
((xlab)){
xlab <- "Effect"
}
}
# Wait time
((wait)){
w <- ((amInputs$wait))
} w <- wait
# Monitoring steps
((steps)){
s <- ((amInputs$steps))
} s <- steps
# Affirmation steps
((affirm)){
a <- ((amInputs$affirm))
} a <- affirm
# Maximum sample size
((N)){
n <- ((amInputs$N))
} n <- N
# Number of lag (delayed) outcomes
(()){
l <- ((amInputs$))
} l <-
# List of monitoring frequency and lag outcomes
mfl <- (wait=w, steps=s, affirm=a, N=n, =l)
mfl_lengths <- (mfl,)
# effects
<- ((((am),FUN = (x) ((x,="_")[1]][2]))))
# Ensure all, or all but one, parameter(s) held constant
( (mfl_lengths==1) < 4){
(mfl)
("Set all, or all but one, monitoring frequency or lag (delayed) settings to a single value.")
} {
whichVary <- (mfl_lengths>1)
nVariations <- mfl_lengths[whichVary]
((whichVary)==0){
nVariations <- 1
}
y <- (=(),=nVariations)
(te 1:()){
o <- am[paste0(effectX,"_",[te])]]"mcmcOC"]]
y[te,] <- o[o,"wait"] %in% mfl"wait"]] &
o,"steps"] %in% mfl"steps"]] &
o,"affirm"] %in% mfl"affirm"]] &
o,"N"] %in% mfl"N"]] &
o,"lag"] %in% mfl"lag"]], stat]
}
}
# Main header
(( = "rejH0",x = stat)){
main <- "P( reject H0 )"
} if ((="cover", x = stat)){
main <- "Interval Coverage"
} if (stat=="n" | stat=="lag.n"){
main <- "Average Sample Size"
} if ((="mse",x = stat)){
main <- "MSE"
} if ((="bias",x = stat)){
main <- "Bias (standardized by SD)"
} ((="stopInconclusive", x = stat)){
main <- "P( inconclusive )"
} ((="stopNotROPE",x = stat)){
main <- "P( not ROPE )"
} ((="stopNotROME", x= stat)){
main <- "P( not ROME )"
} ((="stopInconsistent", x = stat)){
main <- "P( Conclusion changed after lagged outcomes )"
} {
main <- ""
}
(addMain) {
figMain <- (main,"\n",
(((((mfl[which(mfl_lengths==1)])),=1, = 1)),
" = ",
(mfl[which(mfl_lengths==1)]), collapse=", "))
} {
figMain <-
}
# Set colors
(nVariations >= 3) {
cols <- RColorBrewer::brewer.pal(nVariations, ="Set1")
} {
cols <- 1:nVariations
}
# Plot boundaries
((amInputs$allocation) == 1){
# If baseline effect is scalar, then it is the same for all simulations
# -- Use last mcmcOC object (o) to obtain scalar
((amInputs$effectGenArgs)==0){
theta0 <- o[1,"theta0"]
}
<- () + theta0
}
(()) <- (())
(()) <- (y)
((())==1){
[2] <- [1] + 1.25 * [1]
}
(!(setMargins)){
(mar=setMargins)
} {
margins <- ("mar")
if (addLegend & nVariations>1){
margins[4] <- margins[4] + 4
} if (addMain){
margins[3] <- margins[3] + 1
}
(mar=margins)
}
# Blank plot
(!()){
(x=1,y=0,=,=,="n",
las=1, xlab=xlab, ylab=ylab,
main=figMain, =, )
} {
(x=0,y=0,=,=,="n",
las=1, xlab=xlab, ylab=ylab,
main=figMain, )
}
(addRegions){
# Colors for figures
cbPalette <- ("#d0d7e8","#f7f5f3", "#e8dbd0")
cbAlpha <- (cbPalette,sep = "40")
# Shade clinically meaningful zones
xLimBuff1 <- () - (())
xLimBuff2 <- () + (())
yLimBuff1 <- () - (())
yLimBuff2 <- () + (())
# When plotting on the log scale, set lower plotting region bound to just greater than zero
(!()){
(=="x"){
(xLimBuff1<0) xLimBuff1 <- 0.001
(xLimBuff2<0) xLimBuff2 <- 0.001
} if (=="y"){
(yLimBuff1<0) yLimBuff1 <- 0.001
(yLimBuff2<0) yLimBuff2 <- 0.001
}
}
dL2 <- amInputs"PRISM"]]"deltaL2"]
dL1 <- amInputs"PRISM"]]"deltaL1"]
dG1 <- amInputs"PRISM"]]"deltaG1"]
dG2 <- amInputs"PRISM"]]"deltaG2"]
# ROME
(x=(xLimBuff1, xLimBuff1, dL2, dL2), y=(yLimBuff1,yLimBuff2,yLimBuff2,yLimBuff1),=cbAlpha[3], xpd=, border=)
(x=(xLimBuff2, xLimBuff2, dG2, dG2), y=(yLimBuff1,yLimBuff2,yLimBuff2,yLimBuff1),=cbAlpha[3], xpd=, border=)
# Grey Zone
(x=(dL2,dL2,dL1,dL1), y=(yLimBuff1,yLimBuff2,yLimBuff2,yLimBuff1),=cbAlpha[2], xpd=, border=)
(x=(dG1,dG1,dG2,dG2), y=(yLimBuff1,yLimBuff2,yLimBuff2,yLimBuff1),=cbAlpha[2], xpd=, border=)
# ROPE / ROWPE
# ROWPE: For figure plotting purposes only, set dL2 (or DG2) from NA to a point beyond plot region
((dL2) & (dL1)) dL1 <- xLimBuff1
((dG2) & (dG1)) dG1 <- xLimBuff2
(x=(dL1,dL1, dG1, dG1), y=(yLimBuff1,yLimBuff2,yLimBuff2,yLimBuff1),=cbPalette[1], border=)
}
(addRegionLines){
# Add line for point null
(v=amInputs$effectPN,lty=2)
(v=(dL2, dL1, dG1, dG2),lwd=2)
}
# Plot stat across effects
for (i 1:(y)){
( x=, y,i], =cols[i], )
}
(nVariations>1){
(x = () + (()) * .35,
y = (),
=mfl[whichVary]],
xjust = 1,
=cols, =19, bty="n",xpd=, = (mfl)[whichVary])
}
# add reference lines
(h=ablineH)
(v=ablineV)
# Reset margins
(mar=(5,4,4,2)+.1)
}
