Response Bias over Time: Interviewer Learning and Missing Data in Egocentric Network Surveys. Issue 4 (November 2017) - Valente, Thomas W.; Dougherty, Leanne; Stammer, Emily
This study investigates potential bias that may arise when surveys include question items for which multiple units are elicited. Examples of such items include questions about experiences with multiple health centers, comparison of different products, or the solicitation of egocentric network data. The larger the number of items asked about each named individual or location, the greater potential interviewer and respondent burden accrues to the naming of more names. Interviewers may be inclined to limit the number of names elicited to reduce the amount of time required to complete the interviews. We tested whether such bias occurred from data collected in northwest Ghana by contrasting group learning with individual learning. The results provided mixed evidence for both group and individual learning and stress the need to take actions such as increased training, change in incentives, and/or monitoring responses to guard against such results.