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Tethering theory to method : using measures of lntraindividual variability to operationalize individuals' dynamic characteristics

posted on 06.12.2017, 00:00 by N Ram, D Conroy, A Pincus, Amanda RebarAmanda Rebar
Within-person changes in behavior that manifest on relatively short timescales are indicative of, and can be used to, measure and model a variety of dynamic constructs. In particular, observations obtained from the same individuals at closely spaced intervals (e.g., seconds, minutes, hours,days, weeks) can be used as indicators of individuals' inherent capacity for change, or dynamic characteristics, and systematic patterns of change that describe behavioral transformations, or dynamic processes (Ram & Gerstorf,2009). Intensive repeated-measures data are a central feature of diary, ecological momentary assessment (EMA), ambulatory, and other intensive longitudinal study designs wherein multiple reports or assessments are obtained over a relatively short span of time (e.g., Bolger, Davis, & Rafaeli,2003; Csikszentmihalyi & Larson, 1987; Shiffman, Stone, & Hufford, 2008;Walls & Schafe r, 2006). In this chapter, we illustrate how quantifications of intraindividual variability, as summaries of intensive repeated-measures data, can be used to examine dynamic characteristics. First, we introduce a set of theories/ constructs (i.e., lability, diversity, polarity, complexity) that can be used to articulate individuals' capacity for change in many domains of inquiry (e.g., emotional experience, interpersonal behavior). Second, we review a set of methods/ mathematical descriptions that, when applied to intensive repeated-measures data, can be used to quantify intraindividual variability. Third, we introduce a set of empirical data and illustrate how the set of theoretical constructs can be explicitly tethered to the mathematical descriptions of those data to examine individuals' dynamic characteristics. Finally, we highlight aspects of theory and study design that hold particular import for the tethering of dynamic constructs to intensive repeated measures data.





Harring JR; Hancock GR

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Information Age Publishing

Place of Publication

Charlotte, NC

Open Access


External Author Affiliations

Pennsylvania State University; TBA Research Institute;

Era Eligible


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