Let’s start with the stated margin of error, which captures sampling variation: error that occurs because surveys are based on only a subset of the full population of likely voters. Even if this sample of respondents is selected randomly from the full population, it is not a perfect representation of attitudes in the full population. That’s where the usual 3 percent error rate comes from.

But the stated margin of error misses other important forms of error. Frame error occurs when there is a mismatch between the people who are possibly included in the poll (the sampling frame) and the true target population.

For example, for phone-based surveys, people without phones would never be included in any sample. Of particular import for election surveys, the sampling frame includes many adults who are not likely to vote. Pollsters try to correct for this by using likely-voter screens — typically asking respondents if they will vote — but this screen itself can introduce error that can at times be larger than the bias it was intended to correct.

And then there is nonresponse error, when the likelihood of responding to a survey is systematically related to how one would have answered the survey. For example, as another one of our papers shows, supporters of the trailing candidate are less likely to respond to surveys, biasing the result in favor of the more popular politician.