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Which Longitudinal Model Should I Choose?

Instats.com now has world-leading statistics and research methods workshops available for livestreaming and on-demand delivery. Head over to Instats.com to see all of their current offerings. This talk by Kenneth Bollen was delivered to the two-day online workshop 'From Data to Causes' sponsored by Humboldt University of Berlin, the University of Melbourne, and the Berlin University Alliance on October 6th and 7th, 2021. Additional information is below. TITLE: Which Longitudinal Model Should I Choose? ABSTRACT: With the growing availability of longitudinal data comes the question of what model to use? In an ideal world, theory and substantive arguments would be sufficiently clear to dictate one. But in practice, there is little guidance and academic fads or the practice in researchers’ fields typically affect model choice. We illustrate how a general longitudinal model (LV-ALT) can help researchers in their selection. The LV-ALT model can specialize to other popular models such as the classic random or fixed effects, growth curve models, autoregressive, latent difference scores, and a variety of other hybrid structures. The LV-ALT model can help to defend the choice of one of these traditional models or it can suggest new hybrid models to consider. We illustrate our results with Add Health NLYS79 data on self reported health and an analysis from a 2021 Demography paper. BIO: Ken Bollen is the Henry Rudolph Immerwahr Distinguished Professor in the Department of Psychology and Neuroscience and Department of Sociology at UNC at Chapel Hill. He is a faculty member in the Quantitative Psychology Program in the Thurstone Psychometric Laboratory. He also is chair of the Methods Core and a Fellow of the Carolina Population Center and a Faculty member of the Center for Developmental Science. Since 1980 he has been an instructor in the ICPSR Summer Program in Quantitative Methods of Social Research. Bollen’s primary areas of statistical research are in structural equation models, longitudinal methods, and latent growth curve models. See more: https://bollen.web.unc.edu/