Tag: proc sgplot

Example 9.20: visualizing Simpson’s paradox

Simpson’s paradox is always amazing to explain to students. What’s bad for one group, and bad for another group is good for everyone, if you just collapse over the grouping variable. Unlike many mathematical paradoxes, this arises in a number of real…

Example 9.2: Transparency and bivariate KDE

In Example 9.1, we showed a binning approach to plotting bivariate relationships in a large data set. Here we show more sophisticated approaches: transparent overplotting and formal two-dimensional kernel density estimation. We use the 10,000 simulat…

Example 9.2: Transparency and bivariate KDE

In Example 9.1, we showed a binning approach to plotting bivariate relationships in a large data set. Here we show more sophisticated approaches: transparent overplotting and formal two-dimensional kernel density estimation. We use the 10,000 simulat…

Example 9.2: Transparency and bivariate KDE

In Example 9.1, we showed a binning approach to plotting bivariate relationships in a large data set. Here we show more sophisticated approaches: transparent overplotting and formal two-dimensional kernel density estimation. We use the 10,000 simulat…

Example 7.42: Testing the proportionality assumption

In addition to the non-parametric tools discussed in recent entries, it’s common to use proportional hazards regression, (section 4.3.1) also called Cox regression, in evaluating survival data.It’s important in such models to test the proportionality a…