Using Factor-Based Plots for Visualization: A Comparative Analysis of Numeric vs Factor Variables.

To modify the code so that it uses a factor variable mapped to the x-axis and still maintains the same appearance, we need to make two changes:

We add another plot (p2) where the Nsubjects2 is used for mapping.
Since there are multiple values in each “bucket”, we don’t want lines to appear on our factor-based plots, so instead we use a boxplot.

Here’s how you could modify your code:

# base plot
p &lt;- ggplot(test_data,
            aes(y = Odds, color=EffectSize)) +
  facet_wrap(DataType ~ ExpType, labeller = label_both, scales = "free")

# plot with numeric variable mapped to x-axis
p1 &lt;- p + aes(x = Nsubjects) +
  geom_line(linewidth = 2) +
  geom_ribbon(aes(ymax = Upper, ymin = Lower, fill = EffectSize), 
              alpha = 0.2)

# plot with factor variable mapped to x-axis (using boxplot)
p2 &lt;- p + aes(x = Nsubjects2) +
  geom_boxplot()

# coord layer
cc &lt;- coord_cartesian_panels(
  panel_limits = tibble::tribble(
    ~DataType, ~ExpType, ~ymin, ~ymax
    , "A"      , "X"     ,     1,     4
    , "A"      , "Y"     ,     1,     6
    , "B"      , "Y"     ,     1,     7
  )
)

# print plots to show that the same coord layer works for both
p1 + ggtitle("Before (numeric x)")
+ cc + ggtitle("After (numeric x)")
p2 + ggtitle("Before (factor x)")
+ cc + ggtitle("After (factor x)")

This will create two separate plots (p1 and p2) with the same appearance as the base plot, but using a numeric variable mapped to the x-axis in one of them, and a factor variable mapped to the x-axis in the other.

Last modified on 2024-01-29