## ----message=FALSE, warning=FALSE, echo=TRUE, eval=TRUE----------------------- ## Load relevant packages library(superb) # for superbPlot library(ggplot2) # for all the graphic directives library(gridExtra) # for grid.arrange ## ----message=FALSE, echo=TRUE, eval=TRUE-------------------------------------- head(dataFigure1) ## ----message=FALSE, echo=TRUE, eval=TRUE, fig.width=3, fig.height=4, fig.cap="**Figure 1a**. Left panel of Figure 1."---- plt1a <- superb( score ~ grp, dataFigure1, plotStyle = "line" ) plt1a ## ----message=FALSE, echo=TRUE, eval=TRUE-------------------------------------- ornateBS <- list( xlab("Group"), ylab("Attitude towards class activities"), scale_x_discrete(labels = c("Collaborative\ngames", "Unstructured\nactivities")), #new! coord_cartesian( ylim = c(70,130) ), geom_hline(yintercept = 100, colour = "black", linewidth = 0.5, linetype=2), theme_light(base_size = 10) + theme( plot.subtitle = element_text(size=12)) ) ## ----message=FALSE, echo=TRUE, eval=TRUE, fig.width=3, fig.height=4, fig.cap="**Figure 1b**. Decorating left panel of Figure 1."---- plt1a <- plt1a + ornateBS + labs(subtitle="(stand-alone)\n95% CI") plt1a ## ----message=FALSE, echo=TRUE, eval=TRUE, fig.width=3, fig.height=4, fig.cap="**Figure 1c**. Making and decorating central panel of Figure 1."---- plt1b <- superb( score ~ grp, dataFigure1, adjustments = list(purpose = "difference"), #new! plotStyle = "line" ) plt1b <- plt1b + ornateBS + labs(subtitle="Difference-adjusted\n95% CI") plt1b ## ----message=FALSE, echo=TRUE, eval=TRUE, fig.width=3, fig.height=4, fig.cap="**Figure 1d**. Making and decorating right panel of Figure 1."---- plt1c <- superb( score ~ grp, dataFigure1, adjustments = list(purpose = "difference"), plotStyle = "raincloud", # new layout! violinParams = list(fill = "green", alpha = 0.2) ) # changed color to the violin plt1c <- plt1c + ornateBS + labs(subtitle="Difference-adjusted\n95% CI") plt1c ## ----message=FALSE, echo=TRUE, eval=TRUE, fig.width=9, fig.height=4, fig.cap="**Figure 1**. The complete Figure 1."---- grid.arrange(plt1a, plt1b, plt1c, ncol=3) ## ----message=FALSE, echo=TRUE, eval=FALSE------------------------------------- # png(filename = "Figure1.png", width = 640, height = 320) # grid.arrange(plt1a, plt1b, plt1c, ncol=3) # dev.off() ## ----message=FALSE, echo=TRUE, eval=TRUE-------------------------------------- t.test(dataFigure1$score[dataFigure1$grp==1], dataFigure1$score[dataFigure1$grp==2], ) ## ----message=FALSE, echo=TRUE, eval=TRUE-------------------------------------- ornateWS <- list( xlab("Moment"), #different! scale_x_discrete(labels=c("Pre\ntreatment", "Post\ntreatment")), ylab("Statistics understanding"), coord_cartesian( ylim = c(75,125) ), geom_hline(yintercept = 100, colour = "black", linewidth = 0.5, linetype=2), theme_light(base_size = 10) + theme( plot.subtitle = element_text(size=12)) ) ## ----------------------------------------------------------------------------- head(dataFigure2) ## ----message=FALSE, echo=TRUE, eval=TRUE, fig.width=3, fig.height=4, fig.cap="**Figure 2a**. Making left panel of Figure 2."---- plt2a <- superb( cbind(pre,post) ~ . , dataFigure2, WSFactors = "Moment(2)", adjustments = list(purpose = "single"), plotStyle = "line" ) plt2a <- plt2a + ornateWS + labs(subtitle="Stand-alone\n95% CI") plt2a ## ----message=TRUE, echo=TRUE, eval=TRUE, fig.width=3, fig.height=4, fig.cap="**Figure 2b**. Making central panel of Figure 2."---- plt2b <- superb( cbind(pre, post) ~ . , dataFigure2, WSFactors = "Moment(2)", adjustments = list(purpose = "difference", decorrelation = "CA"), #new plotStyle = "line" ) plt2b <- plt2b + ornateWS + labs(subtitle="Correlation and difference-\nadjusted 95% CI") plt2b ## ----message=FALSE, echo=TRUE, eval=TRUE, fig.width=3, fig.height=4, fig.cap="**Figure 2c**. Making third panel of Figure 2."---- plt2c <- superb( cbind(pre, post) ~ ., dataFigure2, WSFactors = "Moment(2)", adjustments = list(purpose = "difference", decorrelation = "CA"), plotStyle = "pointindividualline" ) #new plt2c <- plt2c + ornateWS + labs(subtitle="Correlation and difference-\nadjusted 95% CI") plt2c ## ----------------------------------------------------------------------------- ornateWS2 <- list( xlab("Difference"), scale_x_discrete(labels=c("Post minus Pre\ntreatment")), ylab("Statistics understanding"), coord_cartesian( ylim = c(-25,+25) ), geom_hline(yintercept = 0, colour = "black", linewidth = 0.5, linetype=2), theme_light(base_size = 10) + theme( plot.subtitle = element_text(size=12)) ) ## ----message=FALSE, echo=TRUE, eval=TRUE, fig.width=3, fig.height=4, fig.cap="**Figure 2d**. Making right panel of Figure 2."---- dataFigure2$diff <- dataFigure2$post - dataFigure2$pre plt2d <- superb( diff ~ ., dataFigure2, WSFactor = "Moment(1)", adjustments = list(purpose = "single", decorrelation = "none"), plotStyle = "raincloud", violinParams = list(fill = "green") ) #new plt2d <- plt2d + ornateWS2 + labs(subtitle="95% CI \nof the difference") plt2d ## ----message=FALSE, echo=TRUE, eval=TRUE, fig.width=9, fig.height=4, fig.cap="**Figure 2**. The complete Figure 2."---- grid.arrange(plt2a, plt2b, plt2c, plt2d, ncol=4) ## ----message=FALSE, echo=TRUE, eval=FALSE------------------------------------- # png(filename = "Figure2.png", width = 850, height = 320) # grid.arrange(plt2a, plt2b, plt2c, plt2d, ncol=4) # dev.off() ## ----message=FALSE, echo=TRUE, eval=TRUE-------------------------------------- t.test(dataFigure2$pre, dataFigure2$post, paired=TRUE) ## ----message=FALSE, echo=TRUE, eval=TRUE-------------------------------------- ornateCRS <- list( xlab("Group"), ylab("Quality of policies"), scale_x_discrete(labels=c("From various\nfields", "From the\nsame field")), #new! coord_cartesian( ylim = c(75,125) ), geom_hline(yintercept = 100, colour = "black", linewidth = 0.5, linetype=2), theme_light(base_size = 10) + theme( plot.subtitle = element_text(size=12)) ) ## ----message=FALSE, echo=TRUE, eval=TRUE, fig.width=3, fig.height=4, fig.cap="**Figure 3a**. The left panel of Figure 3."---- plt3a <- superb( VD ~ grp, dataFigure3, adjustments = list(purpose = "single", samplingDesign = "SRS"), plotStyle = "line" ) plt3a <- plt3a + ornateCRS + labs(subtitle="Stand-alone\n95% CI") plt3a ## ----message=TRUE, echo=TRUE, eval=TRUE, fig.width=3, fig.height=4, fig.cap="**Figure 3b**. The central panel of Figure 3."---- plt3b <- superb( VD ~ grp, dataFigure3, adjustments = list(purpose = "difference", samplingDesign = "CRS"), #new plotStyle = "line", clusterColumn = "cluster" ) #new plt3b <- plt3b + ornateCRS + labs(subtitle="Cluster and difference-\nadjusted 95% CI") plt3b ## ----message=FALSE, echo=TRUE, eval=TRUE, fig.width=8, fig.height=4, fig.cap="**Figure 3c**. The right panel of Figure 3."---- plt3c <- superb( VD ~ grp, dataFigure3, adjustments = list(purpose = "difference", samplingDesign = "CRS"), plotStyle = "raincloud", violinParams = list(fill = "green", alpha = 0.2), clusterColumn = "cluster" ) plt3c <- plt3c + ornateCRS + labs(subtitle="Cluster and difference-\nadjusted 95% CI") ## ----message=FALSE, echo=TRUE, eval=TRUE, fig.width=8, fig.height=4, fig.cap="**Figure 3**. The complete Figure 3."---- grid.arrange(plt3a, plt3b, plt3c, ncol=3) ## ----message=FALSE, echo=TRUE, eval=FALSE------------------------------------- # png(filename = "Figure3.png", width = 640, height = 320) # grid.arrange(plt3a, plt3b, plt3c, ncol=3) # dev.off() ## ----message=FALSE, echo=TRUE, eval=TRUE-------------------------------------- res <- t.test( dataFigure3$VD[dataFigure3$grp==1], dataFigure3$VD[dataFigure3$grp==2], ) # mean ICCs per group, as given by superbPlot micc <- mean(c(0.491335, 0.203857)) # lambda from five clusters of 5 participants each lambda <- CousineauLaurencelleLambda(c(micc, 5, 5, 5, 5, 5, 5)) tcorrected <- res$statistic / lambda pcorrected <- 1 - pt(tcorrected, 4) cat(paste("t-test corrected for cluster-randomized sampling: t(", 2*(dim(dataFigure3)[1]-2),") = ", round(tcorrected, 3), ", p = ", round(pcorrected, 3),"\n", sep= "")) ## ----message=FALSE, echo=TRUE, eval=TRUE-------------------------------------- ornateBS <- list( xlab(""), ylab("Metabolic score"), scale_x_discrete(labels=c("Response to treatment")), #new! coord_cartesian( ylim = c(75,125) ), geom_hline(yintercept = 100, colour = "black", linewidth = 0.5, linetype=2), theme_light(base_size = 10) + theme( plot.subtitle = element_text(size=12)) ) ## ----message=FALSE, echo=TRUE, eval=TRUE, fig.width=3, fig.height=4, fig.cap="**Figure 4a**. The left panel of Figure 4."---- plt4a <- superb( score ~ group, dataFigure4, adjustments=list(purpose = "single", popSize = Inf), plotStyle="line" ) plt4a <- plt4a + ornateBS + labs(subtitle="Stand-alone\n95% CI") ## ----message=FALSE, echo=TRUE, eval=TRUE, fig.width=3, fig.height=4, fig.cap="**Figure 4b**. The central panel of Figure 3b."---- plt4b <- superb( score ~ group, dataFigure4, adjustments=list(purpose = "single", popSize = 50 ), # new! plotStyle="line" ) plt4b <- plt4b + ornateBS + labs(subtitle="Population size-\nadjusted 95% CI") ## ----message=FALSE, echo=TRUE, eval=TRUE, fig.width=3, fig.height=4, fig.cap="**Figure 4c**. The right panel of Figure 3b."---- plt4c <- superb( score ~ group, dataFigure4, adjustments=list(purpose = "single", popSize = 50 ), # new! plotStyle="pointjitterviolin", violinParams = list(fill = "green", alpha = 0.2) ) plt4c <- plt4c + ornateBS + labs(subtitle="Population size-\nadjusted 95% CI") ## ----message=FALSE, echo=TRUE, eval=TRUE, fig.width=9, fig.height=4, fig.cap="**Figure 4**. The complete Figure 4."---- plt4 <- grid.arrange(plt4a, plt4b, plt4c, ncol=3) ## ----message=FALSE, echo=TRUE, eval=FALSE------------------------------------- # png(filename = "Figure4.png", width = 640, height = 320) # grid.arrange(plt4a, plt4b, plt4c, ncol=3) # dev.off() ## ----message=FALSE, echo=TRUE, eval=TRUE-------------------------------------- res <- t.test(dataFigure4$score, mu=100) tcorrected <- res$statistic /sqrt(1-nrow(dataFigure4) / 50) pcorrected <- 1-pt(tcorrected, 24) cat(paste("t-test corrected for finite-population size: t(", nrow(dataFigure4)-1,") = ", round(tcorrected, 3), ", p = ", round(pcorrected, 3),"\n", sep= ""))