# NOT RUN {
### Show distribution for an event rate value of 125
ggNNC(erDataSeq(threshold=125, mean=90, sd=30));
### If the event occurs under the threshold instead of
### above it
ggNNC(erDataSeq(threshold=125, mean=90, sd=30,
eventIfHigher = FALSE));
### ... And for undesirable events (note how
### desirability is an argument for ggNNC, whereas
### whether an event occurs 'above' or 'below' the
### threshold is an argument for erDataSeq):
ggNNC(erDataSeq(threshold=125, mean=90, sd=30,
eventIfHigher = FALSE),
eventDesirable = FALSE);
### Show event rate for both experimental and
### control conditions, and show the numbers
### needed for change
ggNNC(erDataSeq(threshold=125, mean=90, sd=30), d=.5);
### Illustration of how even with very large effect
### sizes, if the control event rate is very high,
### you'll still need a high number of NNC
ggNNC(erDataSeq(er=.9), d=1);
# }
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