2016 Postmortem
Related: About this forumBreaking Reuters National Poll- Clinton 43% Drumpf 34%
http://elections.huffingtonpost.com/pollster/polls/ipsos-reuters-24596
MADem
(135,425 posts)I think that margin will increase once HRC is the presumptive nominee and Obama can start campaigning for her.
DemocratSinceBirth
(99,710 posts)That would be the biggest Democratic landslide since LBJ's 64 landslide and FDR's first re-election landslide.
democrattotheend
(11,605 posts)I for one am relieved, not disappointed. I want our nominee, whoever it is, to beat Trump. As do most Bernie supporters.
MADem
(135,425 posts)democrattotheend
(11,605 posts)I don't deny that a lot of Bernie supporters really dislike Hillary, but very few of us if any want to see Trump become president.
Joe the Revelator
(14,915 posts)From your own link. Haven't we all agreed that internet polls are not representative?
leftynyc
(26,060 posts)The Bernie supporters have been claiming for over six months that internet polls are important because people have to show their enthusiasm simply by getting in there and voting. I'll wait and see if they're sniveling hypocrites about this poll.
Joe the Revelator
(14,915 posts)Response to Joe the Revelator (Reply #7)
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DemocratSinceBirth
(99,710 posts)But it would only be fair to let him speak for himself.
DemocratSinceBirth
(99,710 posts)I regret that you find trump losing in this particular poll disappointing.
Response to DemocratSinceBirth (Reply #16)
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DemocratSinceBirth
(99,710 posts)MADem
(135,425 posts)take opinion polls on a regular basis, as opposed to just coming across a poll and clicking?
I found an explanation of their methodology in a pop up at their site (see ABOUT), which Reuters says is OK to share (I'm afraid some of it translated a bit wonkily into smilies, sorry--but you can get the gist of it): http://polling.reuters.com/
This Reuters / Ipsos poll began in January 2012 and since then continuously polled between 2,000 and 3,000 people a week. Over that period, we have asked hundreds of questions ranging from presidential politics to the Oscars, from the Syrian civil war to the perception of social networks, such as Facebook and Twitter.
Unlike almost all mainstream polls, the data is entirely collected via online surveys. Online surveys allow us to collect far more data and to be more flexible and fast-moving than phone research, and online is also where the future of polling lies.
This methodology may be different from the traditional (telephone) approach used by others, but it is highly accurate: It was the most accurate national poll of US residents published immediately before the November 2012 general election.
Our data is primarily drawn from online surveys using sampling methods developed in consultation with several outside experts. These involve recruiting respondents from the entire population of US-based Internet users in addition to hundreds of thousands of individuals pre-screened by Ipsos. In line with industry practice, some of these respondents are awarded points for participating. Those points can be redeemed for various rewards. The responses are then weighted based on demographic information.
Because of the volume of demographic information collected, the poll provides unprecedented insight into the myriad of communities that constitute the United States in the 21st century.
This window into the population allows users to look at the polling results over time and adjust the aggregated interval of results to maintain a reasonable sample size. Those intervals are five-day rolling average as well as weekly, monthly and overall averages.
The accuracy is measured using Bayesian credibility intervals. For the stats folks among you: the credibility interval assumes that Y has a binomial distribution conditioned on the parameter ?, i.e., Y|?~Bin(n,? , where n is the size of our sample. In this setting, Y counts the number of yes, or 1, observed in the sample, so that the sample mean (y ̅ is a natural estimate of the true population proportion ?. This model is often called the likelihood function, and it is a standard concept in both the Bayesian and the Classical framework.
In the Bayesian framework, ones knowledge base is ones Prior Distribution. For the purposes of this document, ? is a proportion which assumes values between 0 and 1. This may reflect the proportion supporting a particular voter initiative or candidate. The family of prior distributions we are considering assumes a beta distribution, In effect, ? ? ~ß(a,b) is a useful representation of our prior knowledge about the proportion ?. The quantities a and b are called hyper-parameters, and are used to express/model ones prior opinion about ?.
In other words, judicial choice of a and b can restate ones belief that the parameter is nearer to 25% (a=1 and b=3), near to 50% (a=1 and b=1) or nearer to 75% (a=3 and b=1). The choices of a and b also defines the shape of the probability curve, with a=1 and b=1 denoting a uniform or flat distribution. In effect, this is equivalent to believing that the true value of ? has the same chance of being any value between 0 and 1.
The hyper-parameters a and b are not limited to a known constant. They too can be modeled as random quantities. This adds flexibility to the model, and it allows for data-based approaches to be considered, such as Empirical and Hierarchical Bayes.
The posterior distribution in Bayesian statistics takes the likelihood function and combines it with our prior distribution. Using our prior Beta distribution, the posterior distribution is also a beta distribution (? ?/y) ~ ß (y+a,ny+b)). It is the hyper-parameters of the prior distribution, i.e., ones knowledge base, updated using the latest survey information9. In other words, the posterior distribution represents our opinion on which are the plausible values for ? adjusted after observing the sample data.
Our credibility interval for ? is based on this posterior distribution. As mentioned above, these intervals represent our belief about which are the most plausible values for ? given our updated knowledge base.
There are different ways to calculate these intervals based on ? ?/y). One approach is to create an estimator analogous to what is done within the Classical framework. In this case, the credible interval for any observed sample is based on a prior distribution that does not include information from our knowledge base. This case occurs when we assume that the parameters of the beta distribution are a=1, b=1 and y=n/2.
Essentially, these choices provide a uniform prior distribution where the value of ? is equally likely on the range between 0 and 1. In effect, our knowledge base is equally sure or unsure that the true value is near zero, 25%, 50%, 75% or 100%. The confidence interval is usually calculated assuming a normal distribution.
However when we are measuring a proportion, and the estimate of the proportion is close to one or zero, this approach is no longer accurate. Therefore we use a logit transform of the proportion and estimate its confidence interval, then invert to calculate the confidence interval of the proportion.
Please enjoy and share. If you have any questions, please contact me, Chris Kahn, U.S. Polling Editor
leftynyc
(26,060 posts)but yours is an interesting post. Other than posting to negate the ridiculous "her polling is falling off a cliff" hysteria stories, I pretty much ignore general election polls this far out.
MADem
(135,425 posts)When Obama and others start serving as surrogates, the game is going to change a lot, I suspect.
My purpose in presenting that "About Reuters Polling" bit was to counteract the "meaningless online polls" charge. I think regular Reuters readers are the "universe" of those polled, and they are invited to join that universe. So it's not entirely random, the universe, even though those who choose to respond w/in that universe might be randomly (self) selected.
leftynyc
(26,060 posts)to seeing Pres Obama campaign. He's masterful at it and it'll be a very striking contrast between who we have as President and the pathetic worm donnie who wants his job. Nobody does the subtle mocking like Pres Obama and the only way to beat donnie is with mocking.
MADem
(135,425 posts)He mocked The Donald into running for POTUS at the correspondent's dinner! Mister Long Form Birth Certificate! LOL!
This is worth seeing again!!!!
leftynyc
(26,060 posts)It NEVER gets old.
DemocratSinceBirth
(99,710 posts)However this a weighted polls with controls to approximate a random sample:
Gender
Age
Education
Ethnicity
http://big.assets.huffingtonpost.com/2016ReutersTrackingCorePolitical60116.pdf
MariaThinks
(2,495 posts)NurseJackie
(42,862 posts)Surya Gayatri
(15,445 posts)SheenaR
(2,052 posts)Sanders defeats Trump - GE polls do not matter
Clinton defeats Trump- Let's go nuts
Response to DemocratSinceBirth (Original post)
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DemocratSinceBirth
(99,710 posts)Trump probably won't be putting screen caps on his twitter page.
geek tragedy
(68,868 posts)DemocratSinceBirth
(99,710 posts)geek tragedy
(68,868 posts)DemocratSinceBirth
(99,710 posts)Rex
(65,616 posts)The GOPukers are about to be in for a royal embarrassment.
DemocratSinceBirth
(99,710 posts)Rex
(65,616 posts)CrowCityDem
(2,348 posts)Stuckinthebush
(10,845 posts)Sad
geek tragedy
(68,868 posts)but expressing fear that she will lose.
real coherent
Rex
(65,616 posts)Both nominees can easily beat Dump and HRC only needs a few more delegates. You do the math.
Peacetrain
(22,877 posts)realmirage
(2,117 posts)Once Obama jumps in and even the trump trolls online admit Hillary is the nominee, Trump is toast
BlueNoMatterWho
(880 posts)Question, what is the voter affiliation breakdown in general? I see that this polled 40% Democrats to 27% Rethugs.
MadBadger
(24,089 posts)That is a trend no matter what.
tritsofme
(17,379 posts)Nice result, but I don't give it much credence.