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Note that these polls are of Likely Voters. A big source of systematic error in 2016 state polls was Likely Voter models, used to weight raw poll results by vot
by comicjk 6y ago
Note that these polls are of Likely Voters. A big source of systematic error in 2016 state polls was Likely Voter models, used to weight raw poll results by voting propensity. In the Midwest in 2016, lots of people without college degrees said they preferred Trump - but based on previous elections, pollsters expected few would vote. This kind of shift is hard to predict - pollsters do not intend to make the same mistake again, but they might make another. (National polls are much less noisy because these kinds of regional errors often cancel out when averaged over the country.)
- jeffbee 6y agoSo do 538 and The Economist try to take these polls, back out their biases, and reapply different ones? Or, to borrow a phrase from Trump, "unskew" them?
- comicjk 6y agoNo, these models weight the polls by quality (variously judged), they don't reweight by voter. This weighted average of polls is then used, along with factors like time until the election and economic conditions, to give a probability distribution over election outcomes (which no poll can give you, no matter how you weight it). "Unskewing" polls dates back to 2012 (Dean Chambers and UnskewedPolls.com). He was doing what you describe - applying his own likely voter model to all polls, based on party affiliation. It did not work. Better to use each pollster's likely voter model as it is, since then you have an ensemble and possible cancelation of error.