Demographic household surveys frequently seek the same set of information from all adult household members. An issue for questionnaire designers is how best to collect data about each person without compromising data quality or lengthening the survey. One design strategy is the person-level approach, in which all questions are asked person by person. An alternative approach uses household-level screening questions to identify whether anyone in the household has the characteristic of interest, and then identifies specific individuals. Common wisdom holds that the person-level approach is more thorough. Household-level screening questions offer important efficiencies, since they often present a question only once per household, but may be suspect with regard to data quality. Little research exists comparing these two design strategies.
This paper presents results from Census Bureau’s 1999 Questionnaire Design Experimental Research Survey, which included a split-ballot test comparing person-level questions to household-level questions. We find some evidence that the use of a household screener entails an increased risk of under-reporting relative to a person-level design for some topic areas. We also find evidence, however, that the household-level approach produces more reliable data than the person-level approach for most topic areas. Item nonresponse is generally trivial in both treatments. Behavior coding results showed no inherent superiority of one or the other design. We do find the expected increase in interview efficiency with the household-level design, and some evidence that interviewers preferred it. We conclude with a brief discussion of the implications of these findings, and suggestions for further research.
