What causes nonresponse bias and how can it be mitigated?

• A. Measurement error from instruments; mitigation: calibration
• B. Confounding from baseline differences; mitigation: randomization
• C. Data entry errors; mitigation: double data entry
• D. Differences between respondents and nonrespondents; mitigation: follow-up, incentives, weighting adjustments

Answer: (D)

Nonresponse bias happens when the people who respond to a survey differ in important ways from those who don’t respond, and those differences are related to what you’re measuring. If the characteristics that distinguish respondents from nonrespondents also influence the outcomes of interest, the results won’t accurately reflect the target population. To mitigate this, start by boosting how often people respond: follow up with nonrespondents, use multiple modes of data collection (phone, mail, online), and offer incentives to participate. If some nonresponse persists, apply weighting adjustments so the respondent sample better matches the population on known characteristics (for example, age, gender, race/ethnicity) through post-stratification or raking. This helps correct the estimates by giving more weight to underrepresented groups. In contrast, the other issues describe problems like measurement error from instruments, confounding from baseline differences, or data entry mistakes—different sources of error not tied to who chose to respond.