- German media report that about 10 per cent of all MPs for the Radical Right AfD (state and federal level) are currently investigated by the police. Allegations range from incitement to fraud and tax evasion. In dubio pro and all that, but it’s not exactly what you normally mean by a law & order party, eh?
- A 89-year old “Nazi Grandma” has failed to show up for the start of her prison sentence.
- German school-leaving exam has students discuss the differences between the hopes connected to the British referendum, and the reality of Brexit since. The usual suspects in the UK are predictably outraged.
- Political involvement, cross-pressures, and multi-party identification in Germany – JEPOP journal publishes very cool article by my erstwhile PhD student @sabrinamayer
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.
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 https://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.
In a recent paper, we derive various multinomial measures of bias in public opinion surveys (e.g. pre-election polls). Put differently, with our methodology, you may calculate a scalar measure of survey bias in multi-party elections.
Thanks to Kit Baum over at Boston College, our Stata add-on
surveybias.ado is now available from Statistical Software Components (SSC). The add-on takes as its argument the name of a categorical variable and said variable’s true distribution in the population. For what it’s worth, the program tries to be smart:
surveybias vote, popvalues(900000 1200000 1800000),
surveybias vote, popvalues(0.2307692 0.3076923 0.4615385), and
surveybias vote, popvalues(23.07692 30.76923 46.15385) should all give the same result.
If you don’t have access to the raw data but want to assess survey bias evident in published figures, there is
surveybiasi, an “immediate” command that lets you do stuff like this:
surveybiasi , popvalues(30 40 30) samplevalues(40 40 20) n(1000). Again, you may specify absolute values, relative frequencies, or percentages.
If you want to go ahead and measure survey bias, install
surveybiasi.ado on your computer by typing
ssc install surveybias in your net-aware copy of Stata. And if you use and like our software, please cite our forthcoming Political Analysis paper on the New Multinomial Accuracy Measure for Polling Bias.
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 to the multi-party case. Being the very creative chaps we are, we call this new statistic [drumroll] . We also derive a weighted version of this measure , and statistics to measure bias in favour/against any single party (). 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.