Understanding Participation in a Web-Based Measurement Burst Design: Response Metrics and Predictors of Participation

Abstract

Introduction Measurement burst designs combine short-term and long-term longitudinal methods (e.g., a two-week daily diary study that recurs quarterly) (Nesselroade 1991; Sliwinksi 2008). These designs are of particular interest to researchers studying within-and between-person associations across time. Although these designs can provide rich data regarding day-to-day behavior, participation in a measurement burst design might be more burdensome than participation in a cross-sectional or less intensive longitudinal design (Bolger and Laurenceau 2013; Sliwinski 2008). As a result, researchers should carefully consider unit nonresponse, which occurs when sample members do not provide any information at a given time point. Methods for analyzing measurement burst data (e.g., multilevel models) do not require that sample members are observed at every time point (Raudenbush and Bryk 2002, 199–200; Snijders and Bosker 1999, 52); however, as noted by Snijders and Bosker (1999, 52), " smaller groups will have a smaller influence on the results than the larger groups " (where " groups " in this context are participants and " group size " is defined as the number of observations obtained from each participant). For example, to the extent that females disproportionately respond to the daily surveys, findings about within-person associations might generalize primarily to females. To date, little is known about response patterns in these designs. Specifically, a thorough characterization of response metrics at various stages of the data collection has not yet been documented. Although studies using these designs often mention that differential participation might affect analytic sample representativeness, a better understanding of where in the data collection representation deteriorates is needed. Using data from a measurement burst design examining substance use across the transition out of high school, we present a description of participation throughout the study by adapting response metrics commonly used by panel studies. We then address the following three research questions: