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### autoplot.calibrateType1.R ---
##----------------------------------------------------------------------
## Author: Brice Ozenne
## Created: apr 5 2018 (13:20)
## Version:
## Last-Updated: Jan 11 2022 (16:46)
## By: Brice Ozenne
## Update #: 30
##----------------------------------------------------------------------
##
### Commentary:
##
### Change Log:
##----------------------------------------------------------------------
##
### Code:
## * Documentation
##' @title Graphical Display of the Bias or Type 1 Error
##' @description Graphical display of the bias or type 1 error
##' for the output of \code{\link{calibrateType1}}.
##' @name autoplot_calibrateType1
##'
##' @param object output of \code{\link{calibrateType1}}.
##' @param type [character] if type equals \code{"bias"} the bias will be displayed.
##' Otherwise if it equals \code{"type1error"} the type 1 error will be displayed.
##' @param plot [logical] should the plot be displayed?
##' @param color.threshold [character] the color for the line representing the expected value(s).
##' @param type.bias [character] if type.bias equals \code{"absolute"} the absolute bias will be used.
##' Otherwise if it equals \code{"relative"} the relative bias will be used.
##' Only relevant when type equals \code{"bias"}.
##' @param alpha [numeric, 0-1] the significance threshold to consider.
##' Only relevant when type equals \code{"type1error"}.
##' @param nrow.legend [integer, >0] the number of rows for the legend.
##' Only relevant when type equals \code{"type1error"}.
##' @param name2label [named character vector] the label for the legend.
##' The vector should contain the method names (see details).
##' Only relevant when type equals \code{"type1error"}.
##' @param color [character vector] a vector of colours to be used to color the lines.
##' Only relevant when type equals \code{"type1error"}.
##' @param keep.method [character vector] the methods names for which the type 1 error should be displayed.
##' Only relevant when type equals \code{"type1error"}.
##' @param ... [internal] Only used by the generic method.
##'
##' @details Method names:
##' \itemize{
##' \item \code{p.Ztest}
##' \item \code{p.Satt}
##' \item \code{p.KR}
##' \item \code{p.robustZtest}
##' \item \code{p.robustSatt}
##' \item \code{p.robustKR}
##' }
##' @return An list containing:
##' \itemize{
##' \item plot: a ggplot object.
##' \item data: the dataset used to generate the ggplot object.
##' }
##'
## * plotBias.calibrateType
##' @rdname autoplot_calibrateType1
##' @method autoplot calibrateType1
##' @export
autoplot.calibrateType1 <- function(object, type = "bias", plot = TRUE, color.threshold = "red",
type.bias = "absolute",
alpha = 0.05, nrow.legend = NULL, name2label = NULL, color = NULL, keep.method = NULL,
...){
type <- match.arg(type, choices = c("bias","type1error"))
## ** display bias
if(type == "bias"){
## *** data
type.bias <- match.arg(type.bias, choices = c("absolute","relative"))
if(type.bias == "absolute"){
object$bias$bias.ML <- object$bias$estimate.truth-object$bias$estimate.ML
object$bias$bias.MLcorrect <- object$bias$estimate.truth-object$bias$estimate.MLcorrect
}else if(type.bias == "relative"){
object$bias$bias.ML <- object$bias$estiamte.truth-object$bias$estiamte.ML
object$bias$bias.MLcorrect <- object$bias$estimate.truth-object$bias$estimate.MLcorrect
}
df1 <- cbind(object$bias[,c("n","rep","name","type","bias.ML")], corrected = FALSE)
names(df1)[5] <- "bias"
df2 <- cbind(object$bias[,c("n","rep","name","type","bias.MLcorrect")], corrected = TRUE)
names(df2)[5] <- "bias"
df.gg <- rbind(df1,df2)
## *** display
gg <- ggplot2::ggplot() + ggplot2::geom_boxplot(data = df.gg, aes_string(x = "type", y = "bias"))
gg <- gg + ggplot2::facet_wrap(corrected ~ n, labeller = ggplot2::label_both)
df.line <- data.frame(x = c(-Inf,Inf), y = 0)
gg <- gg + ggplot2::geom_line(data = df.line, aes_string(x = "x", y = "y"), color = color.threshold)
}
## ** display type 1 error
if(type == "type1error"){
df.gg <- summary(object, alpha = alpha, type = type, display = FALSE)
## *** display
if(is.null(keep.method)){
keep.method <- as.character(unique(df.gg$method))
}
if(is.null(name2label)){
name2label <- stats::setNames(unique(paste0(df.gg$statistic,", ",df.gg$correction)),unique(df.gg$method))
}
if(is.null(color)){
## from ggthemes::colorblind_pal()(8)
color <- c("#000000","#E69F00","#56B4E9","#009E73","#F0E442","#0072B2","#D55E00","#CC79A7")
}
label.method <- name2label[keep.method]
n.method <- length(keep.method)
y.range <- range(c(alpha,df.gg$type1error))
gg <- ggplot2::ggplot(df.gg, aes_string(x = "n", y = "type1error", group = "method", color = "method", shape = "method"))
gg <- gg + ggplot2::geom_point(size = 3) + ggplot2::geom_line(size = 2)
gg <- gg + ggplot2::facet_grid(~link, labeller = ggplot2::label_parsed)
gg <- gg + ggplot2::geom_abline(intercept = alpha, slope = 0, color = color.threshold)
gg <- gg + ggplot2::xlab("sample size")
gg <- gg + ggplot2::ylab("type 1 error rate")
gg <- gg + ggplot2::theme(legend.position = "bottom")
gg <- gg + ggplot2::coord_cartesian(ylim = y.range)
if(!is.null(nrow.legend)){
gg <- gg + ggplot2::guides(color = ggplot2::guide_legend(nrow=nrow.legend,byrow=TRUE))
}
gg <- gg + ggplot2::scale_color_manual("",
breaks = keep.method,
label = label.method,
values = color[1:n.method])
gg <- gg + ggplot2::scale_shape_manual("",
breaks = keep.method,
label = label.method,
values = seq(15,by=1,length=n.method))
}
## ** export
if(plot){
print(gg)
}
rownames(df.gg) <- NULL
return(invisible(list(plot = gg,
data = df.gg)))
}
######################################################################
### autoplot.calibrateType1.R ends here
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