TY - JOUR T1 - An experimental evaluation of a stopping rule aimed at maximizing cost-quality trade-offs in surveys JF - Journal of the Royal Statistical Society Series A: Statistics in Society Y1 - 2023 A1 - Wagner, James A1 - Zhang, Xinyu A1 - Elliott, Michael R A1 - Brady T. West A1 - Coffey, Stephanie M AB - Surveys face difficult choices in managing cost-error trade-offs. Stopping rules for surveys have been proposed as a method for managing these trade-offs. A stopping rule will limit effort on a select subset of cases to reduce costs with minimal harm to quality. Previously proposed stopping rules have focused on quality with an implicit assumption that all cases have the same cost. This assumption is unlikely to be true, particularly when some cases will require more effort and, therefore, more costs than others. We propose a new rule that looks at both predicted costs and quality. This rule is tested experimentally against another rule that focuses on stopping cases that are expected to be difficult to recruit. The experiment was conducted on the 2020 data collection of the Health and Retirement Study (HRS). We test both Bayesian and non-Bayesian (maximum-likelihood or ML) versions of the rule. The Bayesian version of the prediction models uses historical data to establish prior information. The Bayesian version led to higher-quality data for roughly the same cost, while the ML version led to small reductions in quality with larger reductions in cost compared to the control rule. ER - TY - JOUR T1 - EVALUATING ITEM NONRESPONSE IN A LIFE HISTORY CALENDAR: AN ANALYSIS OF MEMORY EFFECTS JF - Innovation in Aging Y1 - 2019 A1 - Hu, Mengyao A1 - Melipillán, Roberto A1 - Zhang, Xinyu A1 - Jacqui Smith KW - Memory AB - Memory decline contributes to response inaccuracy and can produce item missing data, especially in retrospective surveys with older adults. Event history calendars, or the life grid approaches, are commonly used to obtain retrospective life history data. As indicated in previous literature, this approach can assist respondents’ memory retrieval. Despite its wide use, the important issue of item nonresponse due to memory effects in life grid questions has received little attention. Autobiographical memory (AM) research has shown that there are two interconnected long-term memory systems: episodic memories of event details from specific remote times in an individual’s life; and semantic memories of the important facts and themes that define an individual’s life history. Episodic and semantic AM may introduce different levels of difficulty in retrieving memory and thus contribute to different levels of missing data. This study examines the effects of both item-level predictors (e.g., types of memories) and respondent-level predictors (e.g., cognitive status, age, and health status) on the likelihood of item missing data in life grid questions. We analyzed missing data in the 2017 Health and Retirement Study (HRS) Life History Mail Survey (n = 3,844), using multilevel logistic regression. The results revealed higher rates of item missing for episodic memories, and that overall respondents’ cognitive status was significantly associated with their likelihood of providing item missing data. Recent residential information was better recalled than childhood information. These results have implications for life course analysis of exposures linked to residential histories. VL - 3 UR - https://doi.org/10.1093/geroni/igz038.3138 ER -