superb (version 0.9.7.8)

dataFigure1: Data for Figure 1

Description

The data, taken from c17superb, is an example where the "stand-alone" 95\% confidence interval of the means returns a result in contradiction with the result of a statistical test. The paradoxical result is resolved by using adjusted confidence intervals, here the different-adjusted confidence interval.

Usage

data(dataFigure1)

Format

An object of class data.frame.

References

Examples

# NOT RUN {
library(ggplot2)
library(gridExtra)
data(dataFigure1)

options(superb.feedback = 'none') # shut down 'warnings' and 'design' interpretation messages

## realize the plot with unadjusted (left) and ajusted (right) 95% confidence intervals
plt1a <- superbPlot(dataFigure1, BSFactors = "grp", 
    adjustments=list(purpose = "single"), 
    variables = c("score"), plotStyle="bar" ) + 
  xlab("Group") + ylab("Score") + labs(title="95% CI\n") +
  coord_cartesian( ylim = c(85,115) ) +
  geom_hline(yintercept = 100, colour = "black", size = 0.5, linetype=2)
plt1b <- superbPlot(dataFigure1, BSFactors = "grp", 
    adjustments=list(purpose = "difference"), 
    variables = c("score"), 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)
plt1  <- grid.arrange(plt1a,plt1b,ncol=2)

## realise the correct t-test to see the discrepancy
t.test(dataFigure1$score[dataFigure1$grp==1], 
       dataFigure1$score[dataFigure1$grp==2],
       var.equal=TRUE)

# }