Nonresponse bias in a longitudinal measurement design examining substance use across the transition out of high school.
Nonresponse bias in a longitudinal measurement design examining substance use across the transition out of high school.
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DOI：
10.1016/j.drugalcdep.2014.07.039
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发表时间：
2014-10-01
影响因子：
4.2
通讯作者：
Patrick, Megan E.
中科院分区：
文献类型：
--
作者：
Griffin, Jamie;Patrick, Megan E.
Intensive longitudinal methods are used to study the daily-level, within-person associations between substance use and its predictors and consequences. By definition, these designs require greater respondent effort than more traditional longitudinal designs, the result of which may be increased unit nonresponse and, more importantly, nonresponse bias. The present study contrasts the nonresponse properties of a measurement burst design with those of a single one-year follow-up (“control”) design, with a particular emphasis on the retention of young adults who did not plan to graduate from college. High school seniors (N=318) from three Midwestern schools completed an in-school baseline survey in spring 2012. Respondents were then randomized into a measurement burst or control group. Four, eight, and twelve months after baseline, young adults in the measurement burst group received a 30-minute follow-up web survey, followed by 14 days of web-based daily surveys. Young adults in the control group received only a 30-minute follow-up web survey twelve months after baseline. Response rates, predictors of nonresponse, and relative nonresponse biases for measures of sociodemographics, college plans, and substance use were compared between the two measurement groups. Compared to the control design, the measurement burst design had greater relative nonresponse bias for statistics measuring substance use, but lower relative nonresponse bias for the statistic measuring college plans. Intensive longitudinal methods have the potential to retain non-college attending young adults during the transition to adulthood. Nonresponse adjustment weights should be used to correct for any detected bias.
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