# NOT RUN {
data(RS.data)
codeNames = c('Data','Technical.Constraints','Performance.Parameters',
'Client.and.Consultant.Requests','Design.Reasoning','Collaboration');
accum = ena.accumulate.data(
units = RS.data[,c("UserName","Condition")],
conversation = RS.data[,c("Condition","GroupName")],
metadata = RS.data[,c("CONFIDENCE.Change","CONFIDENCE.Pre","CONFIDENCE.Post")],
codes = RS.data[,codeNames],
window.size.back = 4
)
set = ena.make.set(
enadata = accum,
rotation.by = ena.rotate.by.mean,
rotation.params = list(
accum$metadata$Condition=="FirstGame",
accum$metadata$Condition=="SecondGame"
)
)
plot = ena.plot(set)
unitNames = set$enadata$units
### Subset rotated points and plot Condition 1 Group Mean
first.game = unitNames$Condition == "FirstGame"
first.game.points = set$points.rotated[first.game,]
plot = ena.plot.group(plot, first.game.points, labels = "FirstGame",
colors = "red", confidence.interval = "box")
### Subset rotated points and plot Condition 2 Group Mean
second.game = unitNames$Condition == "SecondGame"
second.game.points = set$points.rotated[second.game,]
plot = ena.plot.group(plot, second.game.points, labels = "SecondGame",
colors = "blue", confidence.interval = "box")
print(plot);
# }
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