This chart, documenting the change of support for gay marriage in the US on a state-by-state basis, has been doing the rounds of the blogosphere recently (click to enlarge):
The chart is based on a hierarchical model of polling data by Jeff Lax and Justin Philips. They used the glmer function in R to aggregate poll data from various sources and create an “opinion estimate” for each state in three periods: 1994-1996, 2003-4 and 2009-9. It shows clearly how support for gay marriage has been steadily increasing everywhere (with the notable recent exception of Utah), but is generally increasing fastest in those states where some…
This chart, documenting the change of support for gay marriage in the US on a state-by-state basis, has been doing the rounds of the blogosphere recently (click to enlarge):
The chart is based on a hierarchical model of polling data by Jeff Lax and Justin Philips. They used the glmer function in R to aggregate poll data from various sources and create an “opinion estimate” for each state in three periods: 1994-1996, 2003-4 and 2009-9. It shows clearly how support for gay marriage has been steadily increasing everywhere (with the notable recent exception of Utah), but is generally increasing fastest in those states where some same-sex rights have already been conferred. Andrew Gelman provides further detailed commentary of this chart in an op-ed for the political website NewMajority.com. It’s nice to see such in-depth statistical analysis and graphics from R having an impact on political discourse.
