538 Model Megathread

[adrac]

It's in; only a one or two percentage point change.

Edit: One thing to note: NE-02 has gone over the line.

[adrac]

And she is still hardly doing better in the Electoral College than Obama in 2012, much less 2008.

I suspect that will change if we get some state polls this week.

[adrac]

I don't understand how the Martquette poll changes the final probability by .6%. Even adjusting to C +5, the poll still has her winning by more than the model expects her to even after the poll's been added to the database. That goes against how the model uses polling data, right?

[adrac]

What is the uncertainty of the model, given the # of simulations they run?  That is, each time they enter new polls, they apparently run 10,000 simulations based on the latest #s, and that produces (among other things) an overall projected vote margin and win probability.  But let's say they then ran *another* 10,000 simulations with the same input #s but a different random seed?  How different would the results be?  Because if they'd be different, then in theory you could put in a favorable poll for one candidate and it would end up "helping" the other candidate, just because of simulation noise.  But I'm assuming that 10,000 is enough for the simulation noise to be small?

This is purely a statistical noise effect; given Clinton's win percentage of 70% or so, we shouldn't be surprised by jumps of 0.6% or so in Clinton's win percentage just from rerunning the simulations (1 sigma).  If you start looking at individual battlegrounds, we definitely shouldn't be surprised if one of them jumps a percent or two just from statistical noise.

I wouldn't have expected changes that significant with 10,000 trials, although I will say my technical experience in statistics is fairly limited.

[adrac]

What is the uncertainty of the model, given the # of simulations they run?  That is, each time they enter new polls, they apparently run 10,000 simulations based on the latest #s, and that produces (among other things) an overall projected vote margin and win probability.  But let's say they then ran *another* 10,000 simulations with the same input #s but a different random seed?  How different would the results be?  Because if they'd be different, then in theory you could put in a favorable poll for one candidate and it would end up "helping" the other candidate, just because of simulation noise.  But I'm assuming that 10,000 is enough for the simulation noise to be small?

This is purely a statistical noise effect; given Clinton's win percentage of 70% or so, we shouldn't be surprised by jumps of 0.6% or so in Clinton's win percentage just from rerunning the simulations (1 sigma).  If you start looking at individual battlegrounds, we definitely shouldn't be surprised if one of them jumps a percent or two just from statistical noise.

I wouldn't have expected changes that significant with 10,000 trials, although I will say my technical experience in statistics is fairly limited.

Thinking about it some more, I guess it's just Poisson noise.  It's like taking a poll of 10,000 people.  Your margin of error is small, but it's not going to be as low as 0.1%.  You should expect the win probability for one of the candidates to shift by ~0.5% from one set of simulations to the next (meaning that the gap between them will shift by ~1% from one set of simulations to the next).

Which means, yeah, if the win probability changes by about half a percent, it is statistically meaningless.  You would literally expect a shift of that size just from using exactly the same set of polls, but running the simulations a second time.  And given that there are 50 states, there are going to be at least a few states where the simulation creates a big shift, even when the polls haven't changed at all.

Guess so, I'm just mildly surprised that I haven't seen effects like that pointed out before.

And the T+1 Nevada poll gives her .2% nationally too huh.