## European Identities in the Cloud

As previously reported on this blog, my PhD student and I are doing a CATI survey on European Identities. We opted for queXS (an open source CATI front-end for Limesurvey) and chose a solution hosted by the Australian Consortium for Social and Political Research on Amazon’s network.

## Hosted queXS Is Reliable

Initially, we suffered from a few hick-ups that hit the system while interviewing was in full swing: The form would sometimes simply not open at the very beginning of an interview, which understandably drove our interviewers nuts. Support in Australia fixed the problem quickly, but because of the time difference, we had a somewhat anxious night. Voice over IP connectivity was integrated from Australia but provided by a German company. By and large, that worked well, too. We had one major outage but again, after contacting the ACSPR, that was fixed for good.

PCs and Interviewers not yet Virtualised

## Lousy Response Rate Not a Software Problem

The one element that we did not virtualise were the interviewers. We had hired a large group of student helpers, which, with hindsight, was not necessarily a brilliant idea. queXS makes it very easy to track operator performance, and so we could quickly see that some of them generated very, very high refusal rates. They all received initial training and constant supervision from us, but some of them would barely manage to get one twenty-minute interview per four-hour shift. Others managed four or more. Our star and role model was a guy who attends acting school. If I could clone and upload him to the cloud, I would be a very happy chappy.

## Survey Accuracy

The accuracy of pre-election surveys is a matter of considerable debate. Obviously, any rigorous discussion of bias in opinion polls requires a scalar measure of survey accuracy. Martin, Traugott, and Kennedy (2005) propose such a measure $Surveybias Version 1.1 for Stata is out$ for the two-party case, and in our own work (Arzheimer/Evans 2014), Jocelyn Evans and I demonstrate how $Surveybias Version 1.1 for Stata is out$ can be generalised to the multi-party case, giving rise to a new measure $Surveybias Version 1.1 for Stata is out$ (seriously) and some friends $Surveybias Version 1.1 for Stata is out$ and $Surveybias Version 1.1 for Stata is out$:

Arzheimer, Kai and Jocelyn Evans. “A New Multinomial Accuracy Measure for Polling Bias.” Political Analysis 22.1 (2014): 31-44. doi:10.1093/pan/mpt012
In this article, we propose a polling accuracy measure for multi-party elections based on a generalization of Martin, Traugott, and Kennedy s two-party predictive accuracy index. Treating polls as random samples of a voting population, we first estimate an intercept only multinomial logit model to provide proportionate odds measures of each party s share of the vote, and thereby both unweighted and weighted averages of these values as a summary index for poll accuracy. We then propose measures for significance testing, and run a series of simulations to assess possible bias from the resulting folded normal distribution across different sample sizes, finding that bias is small even for polls with small samples. We apply our measure to the 2012 French presidential election polls to demonstrate its applicability in tracking overall polling performance across time and polling organizations. Finally, we demonstrate the practical value of our measure by using it as a dependent variable in an explanatory model of polling accuracy, testing the different possible sources of bias in the French data.

@Article{arzheimer-evans-2013,
author = {Arzheimer, Kai and Evans, Jocelyn},
title = {A New Multinomial Accuracy Measure for Polling Bias },
journal = {Political Analysis},
year = 2014,
abstract = {In this article, we propose a polling accuracy measure for
multi-party elections based on a generalization of Martin,
Traugott, and Kennedy s two-party predictive accuracy index.
Treating polls as random samples of a voting population, we first
estimate an intercept only multinomial logit model to provide
proportionate odds measures of each party s share of the vote, and
thereby both unweighted and weighted averages of these values as a
summary index for poll accuracy. We then propose measures for
significance testing, and run a series of simulations to assess
possible bias from the resulting folded normal distribution across
different sample sizes, finding that bias is small even for polls
with small samples. We apply our measure to the 2012 French
presidential election polls to demonstrate its applicability in
tracking overall polling performance across time and polling
organizations. Finally, we demonstrate the practical value of our
measure by using it as a dependent variable in an explanatory model
of polling accuracy, testing the different possible sources of bias
in the French data.},
keywords = {meth-e},
volume = {22},
number = {1},
pages = {31--44},
url =
{http://pan.oxfordjournals.org/cgi/reprint/mpt012?ijkey=z9z740VU1fZp331&keytype=ref},
doi = {10.1093/pan/mpt012},
data = {http://hdl.handle.net/1902.1/21603},
html =
{http://www.kai-arzheimer.com/new-multinomial-accuracy-measure-for-polling-bias}
}

## The Surveybias Software 1.1

Calculating the accuracy measures is a matter of some algebra. Estimating standard errors is a bit trickier but could be done manually by making use of the relationship between $Surveybias Version 1.1 for Stata is out$ and the multinomial logistic model on the one hand and Stata’s very powerful implementation of the Delta method on the other. But these calculations are error-prone and become tedious rather quickly. This is why we created a suite of user written programs (surveybias, surveybiasi, and surveybiasseries). They do all the necessary legwork and return the estimates of accuracy, complete with standard errors and statistical tests.

Those Were the Days

We have just updated our software. The new version 1.1 of surveybias features some bug fixes, a better mechanism for automagically dealing with convergence problems, better documentation, and a new example data set that compiles information on 152 German pre-election polls conducted between January and September 2013.

surveybias comes with example data from the French presidential election 2012 and the German parliamentary election 2013. From within Stata, type help surveybias, help surveybiasi, and help surveybiasseries to see how you can make use of our software. If I can find the time, I will illustrate the use of surveybias in a mini series of blogs over the next week.

## Updating Surveybias

The new version 1.1 should appear is now on SSC within the next couple of days or so, but the truly impatient can get it now. In your internet-aware copy of Stata (version 11 or later), type

net from http://www.kai-arzheimer.com/stata 

net install surveybias, replace

Or use SSC: ssc install surveybias, replace

Enjoy!

One of my very able PhD students is working on a better instrument for measuring the interaction of national and European identities. Thanks to the generosity of the Fritz Thyssen Stiftung, we can now road-test some of his ideas in a three-wave telephone survey. Fieldwork for the first wave will commence on Monday, and we are rather excited, not least because we are running this survey in our own “studio”, with a large number of student research assistants working as interviewers.

NASA Earth Observatory / Foter / Public domain

In the past, the university had installed the voxco software in a PC lab that was equipped with headsets and landlines. But the program never worked well and became de facto unusable once the service contract waterminated. Looking for alternatives when we moved into a new building, we came across queXS, an open source CATI software that is based on limesurvey. Limesurvey had worked well for us in the past, so we gave queXS a spin and rather liked it. The only remaining problem was that our IT support could not setup the necessary servers and patch them into the university’s voice over ip infrastructure in time (we want to be in the field well before the Euro 2014 campaign takes off in two weeks or so). So we got in touch with ACSPRI, the Australian Consortium for Social and Political Research Incorporated, which offers access to a Amazon cloud-based installation of queXS that can be rented on a monthly basis for a reasonable fee. ACSPRI also helped us to find a German VOIP provider whose network we will use to place the calls.

Now our “studio” is still based in a university PC lab. But this is mostly an issue of convenience, and of easy supervision. In fact, it could be run on laptops or even tablet computers anywhere on the planet. The software is browser-based and hosted in some unknown, unmarked data centre somewhere. Connectivity to German landlines is provided through software in another data centre, and this whole virtualised infrastructure is supported and maintained from the other end of the world. Apart from the headsets, the only tangible part of the studio is a bunch of pen-drives that hold the interviewers’ access codes. Eerie, isn’t it?

The tests went well, but will it work in practice? I’ll keep you posted.

## Measuring Survey Bias

In our recent Political Analysis paper (ungated authors’ version), Jocelyn Evans and I show how Martin, Traugott, and Kennedy’s two-party measure of survey accuracy can be extended to the multi-party case (which is slightly more relevant for comparativists and other people interested in the world outside the US). This extension leads to a series of party-specific measures of bias as well as to two scalar measures of overall survey bias.

Moreover, we demonstrate that our new measures are closely linked to the familiar multinomial logit model (just as the MTK measure is linked to the binomial logit). This demonstration is NOT an exercise in Excruciatingly Boring Algebra. Rather, it leads to a straightforward derivation of standard errors and facilitates the implementation of our methodology in standard statistical packages.

Those Were the Days

## An Update to Our Free Software

We have programmed such an implementation in Stata, and it should not be too difficult to implement our methodology in R (any volunteers?). Our Stata code has been on SSC for a couple of months now but has recently been significantly updated. The new version 1.0 includes various bug fixes to the existing commands surveybias.ado and surveybiasi.ado, slightly better documentation, two toy data sets that should help you getting started with the methodology, and a new command surveybiasseries.ado.

surveybiasseries facilitates comparisons across a series of (pre-election) polls. It expects a data set in which each row corresponds to margins (predicted vote shares) from a survey. Such a dataset can quickly be constructed from published sources. Access to the original data is not required. surveybiasseries calculates the accuracy measures for each poll and stores them in a set of new variables, which can then be used as depended variable(s) in a model of poll accuracy.

## Getting Started with Estimating Survey Bias

The new version of surveybias for Stata should appear be on SSC over the next couple of weeks or so (double check the version number (was 0.65, should now be 1.0) and the release date), but you can install it right now from this website:

net from http://www.kai-arzheimer.com/stata
net install surveybias

To see the new command in action, try this

use fivefrenchsurveys, replace

will load information from five pre-election polls taken during the French presidential campaign (2012) into memory. The vote shares refer to eight candidates that competed in the first round.

surveybiasseries in 1/3 , popvaria(*true) samplev(fh-other) nvar(N) gen(frenchsurveys)

will calculate our accuracy measures and their standard errors for the first three surveys over the full set of candidates.

surveybiasseries in 4/5, popvariables(fhtrue-mptrue) samplevariables(fh-mp) nvar(N) gen(threeparty)

will calculate bias with respect to the three-party vote (i.e. Hollande, Sarkozy, Le Pen) for surveys no. 4 and 5 (vote shares a automatically rescaled to unity, no recoding required). The new variable names start with “frenchsurveys” and “threeparty” and should be otherwise self-explanatory (i.e. threepartybw is $B_w$ for the three party case, and threepartysebw the corresponding standard error). Feel free to plot and model to your heart’s content.

All surveys deviate from the true distributions of the variables, but some more so than others. This is particularly relevant in the context of election studies, where the true distribution of the vote is revealed on election night. Wouldn’t it be nice if one could quantify the bias exhibited by pollster X in their pre-election survey(s), with one single number? Heck, you could even model bias in polls, using RHS variables such as time to election, sample size or sponsor of the survey, coming up with an estimate of the infamous “house effect”,.

Jocelyn Evans and I have developed a method for calculating such a figure by extending Martin, Kennedy and Traugott’s measure $A Scalar Measure for Bias in (Multi Party Pre Election) Surveys$ to the multi-party case. Being the very creative chaps we are, we call this new statistic [drumroll] $A Scalar Measure for Bias in (Multi Party Pre Election) Surveys$. We also derive a weighted version of this measure $A Scalar Measure for Bias in (Multi Party Pre Election) Surveys$, and statistics to measure bias in favour/against any single party ($A Scalar Measure for Bias in (Multi Party Pre Election) Surveys$). Of course, our measures can be applied to the sampling of any categorical variable whose distribution is known.

We fully develop all these goodies (and illustrate their usefulness by analysing bias in French pre-election polls) in a paper that
(to our immense satisfaction) has just been accepted for publication in Political Analysis (replication files to follow).

Our module survebias is a Stata ado file that implements these methods. It should become available from SSC over the summer, giving you convenient access to the new methods. I’ll keep you posted.

Image via Wikipedia

Fails/Pierce 2010 article in Political Research Quarterly 2010 is easily the most interesting paper I have read during the last Academic Year (btw, here are my lecture notes). Ever since the 1950s, mainstream political science has claimed that mass attitudes on democracy matter for the stability of democracy, while the intellectual history of the concept is even older, going back at least to de TocquevilleBut, as Fails and Pierce point out, hardly anyone has ever bothered to test the alleged link between mass attitudes and the quality and stability of democracy. This is exactly what they set out to do, regressing levels of democratic attitudes compiled from dozens of surveys on previous  and succeeding polity scores. As it turns out, levels of democratic attitudes do not explain much, while they seem to follow changes in the polity scores. If these results hold, the Political Culture paradigm would have to be thoroughly modified, to say the least: It’s the elites, stupid.

My students poured a lot of primarily methodological criticism on these findings (I can see my bad influence on them), and I’m not sure that the interpretation of the last (first-differences on first-differences regression) is conclusive. But nonetheless, this is fascinating stuff. I wonder if the big shots will have to say anything interesting about it, or whether they will just ignore the work of two annoying PhD students.

A couple of months ago, 270 of my flock kindly took part in a survey on their student experience. Today, I finally came around to posting the results of said survey, which are of considerable (if localised) interest (in German).

The other day, a (rather clever) student told me that she has no real need for all these stats classes, because she will be a journalist. I told her that the world would be a better place if all journalists underwent compulsory numeracy classes. Here is the proof from my favourite newspaper. How long does it take you to spot the glitch?

Young people in the East Midlands were the most down-to-earth of those surveyed, expecting an annual salary of £33,468 by the time they reached their mid-thirties. However, even this figure is still around £4,000 higher than the average.

Two-thirds of respondents also thought they would own a house by the time they were 25. In reality, only 14% of homeowners are aged 25 or under.

With the rising cost of higher education hitting students hard, recent figures suggest young people will be left with more than £20,000 of debt by the end of their courses. But the poll shows today’s school children do not realise how out of pocket they will actually be: the average expected figure was just half the reality.

http://www.guardian.co.uk/money/2010/mar/30/teenagers-expect-earnings-51000