SSHD Professional Development Webinar
Speaker: Pascal DeBoeck, University of Utah
Moderator: John Geldhof, Oregon State University
Abstract: Time is unlike other dimensions sampled in the social, behavioral, and medical sciences. People and many variables come in distinct units. Between any pair of observations made across time, however, are an arbitrary number of additional samples that could have been sampled. While sampling across time is always discrete, the underlying dimension is continuous. This incongruity has led to differing perspectives on how repeated observations should be modeled. In some common models, the unobserved interstitial samples are ignored, while in other models these unobserved samples are explicitly considered. This presentation will provide an introduction to two perspectives of how repeated observations can be modeled. Substantive data relating longitudinal measures of Anxiety, Depression, and Social Competence will be presented and analyzed using both discrete and continuous perspectives of time. The example will allow for a comparison of the inferences that can be made using these differing perspectives on time.