![IconGems-Print](images/IconGems-Print.png)
Are You Really Who You Say You Are? Two Case Studies Exploring Respondent-Reported Misclassification
Kenneth M. Pick
USDA National Agricultural Statistics Service
Sarah Goodale
USDA National Agricultural Statistics Service
Audra Zakzeski
USDA National Agricultural Statistics Service
For surveys used to estimate population totals, correctly classifying sample units as in-scope or out-of-scope for the survey can have a sizable impact. This paper explores approaches the USDA National Agricultural Statistics Service (NASS) have taken to understand and measure misclassification resulting from respondents reporting their characteristics incorrectly. This respondent-reported misclassification can have a substantial impact on a survey program and the statistical estimates produced from it. For example, the wording of screening questions and how they are administered can determine whether a respondent qualifies or does not qualify for a survey. If a substantial number of respondents are misclassified, population estimates may be severely misstated.