## ----echo = FALSE, warning=FALSE, message = FALSE, results = 'hide'----------- cat("this will be hidden; use for general initializations.\n") library(superb) library(ggplot2) ## ----------------------------------------------------------------------------- grp1 <- c( 56, 54, 73, 46, 59, 62, 55, 53, 77, 60, 69, 66, 63, 62, 53, 82, 74, 70, 65, 70, 72, 65, 56, 58, 83) grp2 <- c( 51, 99, 194, 123, 40, 83, 87, 117, 46, 89, 61, 81, 53, 141, 52, 53, 39, 96, 14, 81, 63, 66, 80, 113, 82) ## ----------------------------------------------------------------------------- dtaHetero <- data.frame( cbind( id = 1:(length(grp1)+length(grp2)), group = c(rep(1,length(grp1)), rep(2, length(grp2)) ), score = c(grp1, grp2) )) head(dtaHetero) ## ----------------------------------------------------------------------------- library(superb) # to make the summary plot library(ggplot2) # for all the graphic directives library(gridExtra) # for grid.arrange ornate = list( xlab("Difference"), scale_x_discrete(labels=c("Pre-\nTreatment","Post-\nTreatment")), ylab("Score"), coord_cartesian( ylim = c(40,+110) ), theme_light(base_size = 10) + theme( plot.subtitle = element_text(size=16)) ) ## ----fig.height=4, fig.width=3, fig.cap = "**Figure 1**. Plot of dtaHerero showing heterogeneous error bars."---- pt <- superb( score ~ group, dtaHetero, adjustments = list(purpose = "difference"), gamma = 0.95, statistic = "mean", errorbar = "CI", plotStyle = "line", lineParams = list(alpha = 0) #the line is made transparent ) + ornate pt ## ----------------------------------------------------------------------------- # Welch's rectified degrees of freedom wdf <- WelchDegreeOfFreedom(dtaHetero, "score","group") ## ----fig.height=4, fig.width=3, fig.cap = "**Figure 2**. Plot of dtaHerero with rectified degree of freedom."---- pw <- superb( score ~ group, dtaHetero, adjustments = list(purpose = "difference"), gamma = c(0.95, wdf), # new! statistic = "mean", errorbar = "CIwithDF", # new! plotStyle = "halfwidthline", lineParams = list(alpha = 0) ) + ornate pw ## ----fig.height=4, fig.width=3, fig.cap = "**Figure 3**. Plot of dtaHerero with rectified degree of freedom and Tryon' difference-adjusted error bars."---- pwt <- superb( score ~ group, dtaHetero, adjustments = list(purpose = "tryon"), #new! gamma = c(0.95, wdf), statistic = "mean", errorbar = "CIwithDF", plotStyle = "halfwidthline", lineParams = list(alpha = 0) )+ ornate pwt ## ----------------------------------------------------------------------------- # get the summary statistics with superbData t <- superb( score ~ group, dtaHetero, adjustments = list(purpose = "difference"), gamma = 0.95, statistic = "mean", errorbar = "CI", showPlot = FALSE ) # keep only the summary statistics: t2 <- t$summaryStatistics # the length is in column "upperwidth", for lines 1 and 2, # so lets do the mean in the square sense: tmean2 <- sqrt( (t2$upperwidth[1]^2 + t2$upperwidth[2]^2)/2 ) ## ----------------------------------------------------------------------------- tmean <- (t2$upperwidth[1] + t2$upperwidth[2] )/2 ## ----------------------------------------------------------------------------- # get the summary statistics with superbData wt <- superb( score ~ group, dtaHetero, adjustments = list(purpose = "tryon"), gamma = c(0.95, wdf), statistic = "mean", errorbar = "CIwithDF", showPlot = FALSE ) wt2 <- wt$summaryStatistics wmean <- (wt2$upperwidth[1]+wt2$upperwidth[2]) / 2 ## ----fig.height=4, fig.width=9, fig.cap = "**Figure 4**. All three plots with relevant markers in red."---- # showing all three plots, with reference lines in red grid.arrange( pt + labs(subtitle="Difference-adjusted 95% CI\n with default degree of freedom") + geom_text( x = 1.15, y = mean(grp1)+(mean(grp2)-mean(grp1))/2, label = "power-2 mean", angle = 90) + geom_text( x = 1.55, y = mean(grp1)+(mean(grp2)-mean(grp1))/2, label = "regular mean", angle = 90) + geom_hline(yintercept = mean(grp1)+(mean(grp2)-mean(grp1))/2-tmean2/2, colour = "red", linewidth = 0.5, linetype=2) + geom_hline(yintercept = mean(grp1)+(mean(grp2)-mean(grp1))/2+tmean2/2, colour = "red", linewidth = 0.5, linetype=2) + # arrow for the power-2 mean geom_segment(arrow = arrow(length =unit(0.4,"cm")), x=1.33, y=mean(grp1)+(mean(grp2)-mean(grp1))/2, xend=1.33, yend=mean(grp1)+(mean(grp2)-mean(grp1))/2+tmean2/2) + geom_segment(arrow = arrow(length =unit(0.4,"cm")), x=1.333, y=mean(grp1)+(mean(grp2)-mean(grp1))/2, xend=1.33, yend=mean(grp1)+(mean(grp2)-mean(grp1))/2-tmean2/2) + # arrow for the regular mean geom_segment(arrow = arrow(length =unit(0.4,"cm")), x=1.66, y=mean(grp1)+(mean(grp2)-mean(grp1))/2, xend=1.66, yend=mean(grp1)+(mean(grp2)-mean(grp1))/2+tmean/2) + geom_segment(arrow = arrow(length =unit(0.4,"cm")), x=1.66, y=mean(grp1)+(mean(grp2)-mean(grp1))/2, xend=1.66, yend=mean(grp1)+(mean(grp2)-mean(grp1))/2-tmean/2), pw + labs(subtitle="Difference-adjusted 95% CI\nwith df from Welch"), pwt + labs(subtitle="Tryon-adjusted 95% CI\nwith df from Welch") + geom_hline(yintercept = mean(grp1)+wt2$upperwidth[1]/2, colour = "red", linewidth = 0.5, linetype=2) + geom_hline(yintercept = mean(grp2)+wt2$lowerwidth[2]/2, colour = "red", linewidth = 0.5, linetype=2), ncol=3) ## ----------------------------------------------------------------------------- t.test( grp1, grp2, var.equal=FALSE)