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## ----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 <- superbPlot(dataFigure1,
BSFactors = "grp",
variables = "score",
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", size = 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 <- superbPlot(dataFigure1,
BSFactors = "grp",
variables = "score",
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 <- superbPlot(dataFigure1,
BSFactors = "grp",
variables = "score",
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 <- superbPlot(dataFigure2,
WSFactors = "Moment(2)",
variables = c("pre","post"),
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 <- superbPlot(dataFigure2,
WSFactors = "Moment(2)",
variables = c("pre","post"),
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 <- superbPlot(dataFigure2,
WSFactors = "Moment(2)",
variables = c("pre","post"),
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$pre
plt2d <- superbPlot(dataFigure2,
WSFactor = "Moment(1)",
variables = c("diff"),
adjustments = list(purpose = "single", decorrelation = "none"),
plotStyle = "raincloud",
violinParams = list(fill = "green") ) #new
plt2d <- plt2d + ornateWS2 + labs(subtitle="95% CI \nof the difference")
plt2d
## ----message=FALSE, echo=TRUE, eval=TRUE, fig.width=9, fig.height=4, fig.cap="**Figure 2**. The complete Figure 2."----
grid.arrange(plt2a, plt2b, plt2c, plt2d, ncol=4)
## ----message=FALSE, echo=TRUE, eval=FALSE-------------------------------------
# png(filename = "Figure2.png", width = 850, height = 320)
# grid.arrange(plt2a, plt2b, plt2c, plt2d, ncol=4)
# dev.off()
## ----message=FALSE, echo=TRUE, eval=TRUE--------------------------------------
t.test(dataFigure2$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 <- superbPlot(dataFigure3,
BSFactors = "grp",
variables = "VD",
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 <- superbPlot(dataFigure3,
BSFactors = "grp",
variables = "VD",
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 <- superbPlot(dataFigure3,
BSFactors = "grp",
variables = "VD",
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 <- superbPlot(dataFigure4,
BSFactors = "group",
variables = "score",
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 <- superbPlot(dataFigure4,
BSFactors = "group",
variables = "score",
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 <- superbPlot(dataFigure4,
BSFactors = "group",
variables = "score",
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= ""))
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