December 10, 2009

Behind the Numbers: Maine and Gay Marriage

Last month, proponents of equal rights for same-sex couples were sorely disappointed at the result of a ballot question in Maine. Adding insult to injury, many pro-equality groups were quite confident on election day due to polling models predicting their victory, only to see an early lead in the precinct returns evaporate as the night dragged on.

Even this writer predicted that the referendum to overturn Maine's law legalizing gay marriage would fail. And most agreed. had "No" to Proposition 1 leading going into Election Day; and Nate Silver of created a model, based on several variables, likewise predicting that Prop 1 would fail.

After the election, Harry Enten '11 went back and looked at Mr. Silver's model. With a lot of data mining and some top-notch statistical skills, Mr. Enten created a linear regression model to predict the outcome of referenda concerning gay marriage much more accurate than that of Mr. Silver. To quote Mr. Enten:

The average difference between the model's predicted support for an amendment in an election and the actual support for the amendment was 2.69% (compared with Silver's 4.46%). Importantly, this difference was greater than 2.00% in only 4 instances (Michigan 2004, Montana 2004, North Dakota 2004, and South Dakota 2006) and greater than 4.00% in only two (Michigan 2004 and North Dakota 2004) [of 25 total observations].

In other words, this model is quite good.

Because of his work and the impressiveness of the model, Mr. Enten was picked up by as a guest pollster. If you're curious about what went wrong in Maine, and how we can best predict races like this in the future, I suggest you check out his entry, and keep an eye out for more of his work in the future.

(For an example of a predictive model gone bad, check this out.)

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