Monday, February 9, 2015

Newspoll 43-57

The Australian's Newspoll from 6-8 February 2015 continues the challenging numbers for the Coalition: with a two-party preferred voting intention of 43 to 57 in Labor's favour.

Dropping these numbers into the Bayesian model yields the following charts and a headline, aggregate TPP voting intention of 44.2 for the Coalition and 55.8 for Labor.





At this point in the blog, it is my normal practice to remind people that I anchor the above Bayesian aggregation with the assumption that the net bias across all of the polling houses sums to zero.

The LOESS model yields 43.7 per cent for the Coalition and 56.3 per cent to Labor.



Both models are suggesting a sizable decline in voting intention for the Coalition since the New Year.

Sunday, February 8, 2015

Galaxy 43-57

Another published poll ahead of (now) Monday's spill motion. Today's Galaxy poll is no change on last week's poll: 43 to the Coalition, 57 to Labor.

I have made a pre-processing change to the Bayesian model. Before I explain that change, let me provide some context. Rather than resurrect my code base from the 2013 Election (I have about 40 or 50 model and processing files in that directory), I decided to code for the 2016 Election from scratch. Which is what I have done.

I had been thinking about the model output, and in particular how choppy that output appeared. To address the choppiness, I added a Henderson moving average. It worked. But it was not the most comfortable solution.

Last night, I noticed that in the lead-up to the 2013 Election, I reduced the sample size for the Morgan polls down to 1000 as an adjustment for the observed over dispersion given the sample size of the Morgan multi-mode polls. I have made this same adjustment for the 2016 models. It has had the effect of reducing the choppiness in the model. But it also means the outlier poll from the middle of 2014 no longer has such influence on the model. Consequently, the middle of 2014 is no longer the Bayesian nadir for the Coalition.

With today's Galaxy poll factored into the mix, the Bayesian model is now reporting the national voting intention at 44.6 to the Coalition, and 55.4 to Labor. This is pretty much the same result as Kevin Bonham, who puts it at 44.4 to 55.6.

Because I have made a change to the model, I will provide a fairly comprehensive set of charts.








Friday, February 6, 2015

Sunday, February 1, 2015

Bayesian updates for Galaxy and IPSOS

Over the weekend we have two new polls. Both cast more light on the political impact of awarding a Knight of the Order of Australia to the Prince Consort: IPSOS (46-54; -2 on the first week of December for the Coalition) and Galaxy (43-57; also -2 for the Coalition on the first week of December). Individually, both polls suggest a movement of voting intention away from the government of two percentage points since the first week of December.

However, the Bayesian model was not convinced. In part, given the small number of polls we have from both these houses, it has responded by adjusting the house bias for these houses. But, to be fair, the January 27 ReachTEL poll only had a one point movement away from the government between 20 November and 27 January. Also the December Morgan poll and the latest Morgan poll show a one point movement in favour of the Coalition. Consequently, the Morgan and ReachTEL results would have mediated the latest IPSOS and Galaxy movements in the Bayesian model.

While the Bayesian model might not have moved as shockingly for the government as the two most recent polls, it is still moving in the wrong direction for the government. If an election was held now, it would be a thumping landslide win for Labor.

As a very rough rule-of-thumb, we can use the cube rule to estimate the number of seats Labor would win with 55 per cent of the two party preferred vote. That estimate is 97 seats.




Updated

  • 5 February 2015 - added maxima, minima and endpoint statistics to the charts (at the request of Andrew Catsaras). Also added an observation based on the cube rule.