Posted on 10/12/2024 10:48:13 AM PDT by TheRef
These poll averages look at every poll's sample and cross-tabs. Nothing goes into the average without determining exactly where bias exists. Bias is corrected before including.
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Click Here to See My Turnout Assumptions | |||||||||||||||||||||||||||||||||||||||||
Battleground States |
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ARIZONA | Trump +2.8 | Trump +2.8 | |||||||||||||||||||||||||||||||||||||||
GEORGIA | Trump +1.5 | Trump +1.6 | |||||||||||||||||||||||||||||||||||||||
MICHIGAN | Trump +1.7 | Trump +1.6 | |||||||||||||||||||||||||||||||||||||||
NEVADA | TIED | Harris +0.3 | |||||||||||||||||||||||||||||||||||||||
N. CAR. | Trump +1.8 | Trump +1.2 | |||||||||||||||||||||||||||||||||||||||
PENN. | Trump +1.1 | Trump +0.7 | |||||||||||||||||||||||||||||||||||||||
WISCONSIN | Trump +0.4 | Harris +0.2 | |||||||||||||||||||||||||||||||||||||||
POLLS ARE ONLY ONE FACTOR, additional factors include my assessment of turnout, 2020 results & exit polls, absence of polling, polling difficulty, primary voting, registrations, in-state operations, media influence, demographic makeup, future likely developments such as planned spending. |
(Excerpt) Read more at freedomwindow.net ...
Nevada Ping!
To add your name to the growing Nevada ping list, FReepmail me...
Source | Arizona | Georgia | Michigan | Nevada | N. Carolina | Pennsylvania | Wisconsin |
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The Ref's Averages | Trump 49.5 (+2.8) - Harris 46.7 | Trump 48.6 (+1.5) - Harris 47.1 | Trump 48.9 (+1.7) - Harris 47.2 | Trump 48.0 (0) - Harris 48.0 | Trump 49.0 (+1.8) - Harris 47.2 | Trump 48.4 (+1.1) - Harris 47.3 | Trump 48.6 (+0.4) - Harris 48.2 |
PJ's Averages | Trump 49.3 (+2.3) - Harris 47.0 | Trump 48.9 (+1.8) - Harris 47.1 | Trump 47.9 (+1.7) - Harris 47.2 | Trump 47.7 - Harris 48.2 (+0.5) | Trump 48.9 (+0.9) - Harris 48.0 | Trump 48.4 (+0.3) - Harris 48.1 | Trump 48.4 (+0.3) - Harris 48.1 |
PJ's Probabilities | Trump 74.7% | Trump 68.9% | Trump 59.3% | Harris 55.7% | Trump 62.3% | Trump 54.8% | Trump 55.4% |
My Monte Carlo model produces this Electoral College result:
Trump 287 - Harris 251, with a 65% probability of Trump winning.
I expect Trump's ECV to grow as new polls keep coming in.
NOTE: The above result is using the New Jersey Polls from end of June that favored Trump. If I give NJ to Harris, the ECV result changes to this:
Trump 277 - Harris 261, with a 60% probability of Trump winning.
If I give NJ to Harris but assume a 1% bias against Trump (adjust Trump +1 and Harris -1), the ECV result changes to this:
Trump 297 - Harris 241, with an 81% probability of Trump winning.
If I give NJ to Harris but assume a 2% bias against Trump (adjust Trump +2 and Harris -2), the ECV result changes to this:
Trump 313 - Harris 225, with an 93% probability of Trump winning.
-PJ
Sorry, but I can’t / won’t respond to polls.
It feels much too much like divulging troop deployments to the enemy.
[They] will know how many of us have awakened to all [their] gaslighting,
shortly after the only poll that truly matters.
Yes, I agree that older polls should matter less. I actually take them out of my average altogether. My approach is use the data the pollsters give you in the cross-tabs, shape that data with the right voter sample assumptions, then you’ve got something. The problem is dishonest pollsters like NYT/Sienna coming out with that nonsense PA poll today, and the Arizona one for that matter. They actually have Harris trailing by only five with men in PA, and by on three with white ID in PA. Give me a break! Can’t do much with polls like that. All you can do is adjust using party ID in a case like that because the bad party ID impacts all other categories. I like your model. do you put it on a website or just forums like this?
Nice work, TheRef.
Interesting observations, PJ2.
My model is a simple (for me) Excel spreadsheet. I developed a formula in 2010 that converts a poll and margin of error into a probability of the leader actually winning. Nate Silver figured out the same formula in 2012 and built his fivethirtyeight website around it.
I collect up to 15 distinct polls per state, convert each to a probability, date-weight the probabilities into an overall state average, and then run a Monte Carlo simulation of 5,000 iterations to generate an outcome probability distribution.
New polls replace older polls by the same pollster. At this point in the election, I no longer use Registered Voter polls. I used to put out a weekly report here on Free Republic showing the changes in polls for the week, but I stopped putting that much effort into it due to the impacts of systemic voter fraud and push-poll bias. Now I just post snippets like today when an appropriate thread pops up.
I also do a Senate poll. As of now, Republicans have an 82.1% probability of winning the Senate, with an expected value of 51.79 seats.
Regarding adjusting for bias, I leave that to the "experts." I figure that extreme polling error will get washed out in the averages, especially if an outlier poll becomes stale against newer polls. I chose to make my report be on the polls as they are, since that tells a story, too. Hopefully, it ends up being the right one.
-PJ
I’ll keep an eye out for your posts. How do you adjust for toplines that are impacted by biased sampling? It could come in the margin of error calculation you do perhaps. My problem with Nate Silver is the garbage in garbage out problem. If you input the toplines of 80% of polls that are oversampling Dem leaners just a little bit in every ID, like slightly too many women, slightly too many non-white ID, slightly too little white ID, slightly too many college degrees/post-grads, etc. and they don’t balance those out with comparable oversamples of GOP-leaning bias in other categories, won’t your model end up leaning too Dem? Maybe you take a cross section of polls where you have a even number of GOP-leaning and Dem-leaning polls.
My hope was that, over the entire breadth of the polls it would balance out. In 2020, Emerson's polls were the most balanced while Quinnipiac's were the most tilted to Democrats. If I see an egregious error in the sample, I will exclude that poll from the average, but that's as far as I go to try to "correct" the polls.
I had hoped that peer pressure and social stigma from wildly incorrect polls would self-police the polling firms, based on their wanting to remain credible from a business model perspective.
-PJ
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