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Comparing Survey Sampling Strategies: Random-Digit Dial vs. Voter Files

Pew – “Despite sparseness of telephone numbers, a national registration-based poll yielded estimates on par with a parallel random-digit-dial poll: “A new telephone survey experiment finds that, despite major structural differences, an opinion poll drawn from a commercial voter file can produce results similar to those from a sample based on random-digit-dialing (RDD). The study intentionally pushed the boundaries of current polling practices by employing a voter file and a registration-based sampling (RBS) approach as the basis of a full national sample. While voter files are widely used for election surveys at the state and local level, relatively few pollsters have employed them for national surveys. As a result, there are few settled best practices for how to draw national samples from voter files and how to handle missing phone numbers. The study also tackles the question of how successful voter files are in representing Americans as a whole, including those who are not registered to vote. This research was possible because voter file vendors are increasingly trying to provide coverage of all U.S. adults, including those who are not registered to vote, by combining state voter rolls with other commercially available databases. On the large majority of survey questions compared (56 of 65), RBS and RDD polls produced estimates that were statistically indistinguishable. Where the polls differed, the RBS results tilted somewhat more Democratic than the RDD results. An analysis of survey participation among registered voters in the RBS sample found that any partisan differences between RDD and RBS surveys are unlikely to be the result of too many Democrats responding. In fact, the set of confirmed registered voters who participated in the RBS survey were somewhat more Republican than the national voter file as a whole in terms of their modeled partisanship (38% vs. 33%, respectively). The routine demographic weighting applied to the sample corrected most of this overrepresentation…” [h/t Pete Weiss]

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