Just how badly biased is your pre-election survey? Once the election results are in, our scalar measures B and B_w provide convenient, single number summaries. Our surveybias add-on for Stata will calculate these and other measures from either raw data or from published margins. Its latest iteration (version 1.4) has just appeared on SSC. Surveybias 1.4 improves on the previous version by ditching the last remnants of the old numerical approximation code for calculating standard errors and is hence much faster in many applications. Install it now from within Stata by typing
We have updated our add-on (or ado) surveybias, which calculates our multinomial generalisation of the old Martin, Traugott, and Kennedy (2005) measure for survey bias. If you have any dichotomous or multinomial variable in your survey whose true distribution is known (e.g. from the census, electoral counts, or other official data), surveybias can tell you just how badly damaged your sample really is with respect to that variable. Our software makes it trivially easy to asses bias in any survey.
Within Stata, you can install/update surveybias by entering ssc install surveybias. We’ve also created a separate page with more information on how to use surveybias, including a number of worked examples.
The new version is called 1.3b (please don’t ask). New features and improvements include:
Support for (some) complex variance estimators including Stata’s survey estimator (sample points, strata, survey weights etc.)
Improvements to the numerical approximation. survebias is roughly seven times faster now
A new analytical method for simple random samples that is even faster
Convenience options for naming variables created by survebiasseries
Lots of bug fixes and improvements to the code
If you need to quantify survey bias, give it a spin.