Question wording bias

Question wording bias sits in the instrument, not in the sample. The right people were selected and every one of them answered; the answers lean because of how the question was put. That makes it one kind of response bias, and its signature is that two wordings of the same underlying question, put to two equivalent random samples, come back with different answers.

Here are two versions of one question about the same school policy.

• Do you support a ban on phone use during class, so that students are not distracted during lessons?
• Do you support a ban on phone use during class, even though it would stop students reaching a parent in an emergency?

Split 800 students at random, 400 to each version. Suppose the first returns $\hat{p} = 0.61$ in favor and the second $0.38$. Each survey's own 95 percent margin of error is about 0.048, so the gap of 0.23 is roughly five times either one, and the standard error of the difference is 0.034, putting the gap almost 7 standard errors out. Chance did not produce that. The neutral version, "do you support a ban on phone use during class?", is the one that estimates anything.

The wrong diagnosis is "the sample was not representative," or "they should have surveyed more students." Everybody selected answered, so nobody is missing, and asking the loaded question of 4,000 students returns the same lean with a narrower interval around it. The lean lives in the instrument, so only the instrument fixes it.

Not every wording problem is this one. A double-barreled question, such as asking whether people support raising taxes to fund parks and libraries, produces answers nobody can interpret, since a yes and a no each cover two positions; that is confusion rather than a push in one direction. Question order pushes in a direction, and a sensitive question asked face to face pulls toward the socially acceptable answer whatever words it uses.

Potential problems with sampling is topic 1.12 in Unit 1.