dataFigure3: Data for Figure 3 In superb: Summary Plots with Adjusted Error Bars

Description

The data, inspired from \insertCitecl16superb, is an example where the "stand-alone" 95\ a result in contradiction with the result of a statistical test. The paradoxical result is resolved by using adjusted confidence intervals, here the cluster- and different-adjusted confidence interval.

Usage

 1 data(dataFigure3)

Format

An object of class data.frame.

\insertAllCited

Examples

 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 library(ggplot2) library(gridExtra) data(dataFigure3) options(superb.feedback = 'none') # shut down 'warnings' and 'design' interpretation messages ## realize the plot with unadjusted (left) and ajusted (right) 95% confidence intervals plt3a <- superbPlot(dataFigure3, BSFactors = "grp", adjustments=list(purpose = "difference", samplingDesign = "SRS"), variables = c("VD"), plotStyle="bar" ) + xlab("Group") + ylab("Score") + labs(title="Difference-adjusted 95% CI\n") + coord_cartesian( ylim = c(85,115) ) + geom_hline(yintercept = 100, colour = "black", size = 0.5, linetype=2) plt3b <- superbPlot(dataFigure3, BSFactors = "grp", adjustments=list(purpose = "difference", samplingDesign = "CRS"), variables = c("VD"), plotStyle="bar", clusterColumn = "cluster" ) + xlab("Group") + ylab("Score") + labs(title="Cluster and difference-adjusted\n95% CI") + coord_cartesian( ylim = c(85,115) ) + geom_hline(yintercept = 100, colour = "black", size = 0.5, linetype=2) plt3 <- grid.arrange(plt3a,plt3b,ncol=2) ## realise the correct t-test to see the discrepancy res <- t.test(dataFigure3\$VD[dataFigure3\$grp==1], dataFigure3\$VD[dataFigure3\$grp==2], var.equal=TRUE) micc <- mean(c(0.491334683772226, 0.20385744842838)) # mean ICC given by superbPlot lam <- CousineauLaurencelleLambda(c(micc, 5,5,5,5,5,5)) tcorr <- res\$statistic / lam pcorr <- 1-pt(tcorr,4)

superb documentation built on June 23, 2021, 9:08 a.m.