# Visualizing Odds Ratios

Oct 24, 2015 · 1 minute readRdataviz

Although I haven’t had a chance to write it up yet, I like to use dot plots with confidence intervals to visualize regression results, as well. For example, here’s a figure from a recent paper (click to open in a new window):

I like how this figure compactly presents four models, allowing for easy comparison. It’s a nice complement to regression tables.

Logistic regression presents a problem for this type of graph because they typically should plotted on log scales, not linear. Fortunately, this is pretty easy to do in R and ggplot2. The trick is to use `coord_trans(x = “log10”)`

to transform the axis. There are other ways to do it (e.g., `scale_x_log10()`

), but this works with using `scale_x_continuous`

to set the tick marks and labels.

Here’s an example (click to open in a new window):

And here’s the code:

library(ggplot2) # Create labels boxLabels = c("Past encounter", "Mutualism WVO:\nNon-hunting wildlife experiences", "Domination WVO:\nEthics of hunting", "Domination WVO:\nWildlife management", "Age", "Education", "Negative attitudes toward box turtles", "Gender") # Enter summary data. boxOdds are the odds ratios (calculated elsewhere), boxCILow is the lower bound of the CI, boxCIHigh is the upper bound. df <- data.frame( yAxis = length(boxLabels):1, boxOdds = c(2.23189,1.315737,1.22866,.8197413,.9802449,.9786673,.6559005,.5929812), boxCILow = c(.7543566,1.016,.9674772,.6463458,.9643047,.864922,.4965308,.3572142), boxCIHigh = c(6.603418,1.703902,1.560353,1.039654,.9964486,1.107371,.8664225,.9843584) ) # Plot p <- ggplot(df, aes(x = boxOdds, y = yAxis)) p + geom_vline(aes(xintercept = 1), size = .25, linetype = "dashed") + geom_errorbarh(aes(xmax = boxCIHigh, xmin = boxCILow), size = .5, height = .2, color = "gray50") + geom_point(size = 3.5, color = "orange") + theme_bw() + theme(panel.grid.minor = element_blank()) + scale_y_continuous(breaks = yAxis, labels = boxLabels) + scale_x_continuous(breaks = seq(0,7,1) ) + coord_trans(x = "log10") + ylab("") + xlab("Odds ratio (log scale)") + annotate(geom = "text", y =1.1, x = 3.5, label ="Model p < 0.001\nPseudo R^2 = 0.10", size = 3.5, hjust = 0) + ggtitle("Intention to remove box turtles from the road")