library(reshape2)
#Code below melts four columns from a wide data set into four in a long data set
#ID and Gender appear on both lines for each participant (that's why they are id.vars)
#A "variable" column denotes whether the variable is pretest (ScCurrentEv1) or posttest (ScCurrentEv2)
#A "value" column includes the value of the DV at each occasion

## Loading required package: lattice

## Loading required package: survival

## Loading required package: Formula

## 
## Attaching package: 'Hmisc'

## The following objects are masked from 'package:base':
## 
##     format.pval, units

currlong <- melt(Wk07[,c("ID","Gender","ScCurrentEv1","ScCurrentEv2")], 
                 id.vars=c("ID","Gender")) 

#Bonus: How to then plot that two occasion data set:
library(Hmisc)
library(ggplot2)
ggplot(currlong, aes(x=variable, y=value, colour=Gender,
                   group=Gender)) + 
  stat_summary(fun = mean, 
               geom = "point") + 
  stat_summary(fun.data = mean_cl_normal,  
               geom = "errorbar",width=0.2, fun.args=list(mult=1.96),size=1) +
  geom_smooth(method='lm', formula= y~x, size=1,se=FALSE)+
  labs(title = "Prepost current event change in men and women", 
       x= "Occasion (Pretest, Posttest)", 
       y="Current Event Knowledge (scale score)") + 
  theme_bw() + 
  theme(text=element_text(size=10))