Epidemiology, health policy and outcomes
Liubov Arbeeva, MSc
University of North Carolina, Chapel Hill
Carrboro, NC, United States
Disclosure(s): No financial relationships with ineligible companies to disclose
Jamie Collins, PhD
Brigham and Women's Hospital
Boston, MA, United States
Disclosure(s): No relevant disclosure to display
Louise Thoma, PhD, DPT
University of North Carolina
Chapel Hill, NC, United States
Disclosure(s): No financial relationships with ineligible companies to disclose
The goals of the session include: provide a nontechnical overview of specific methods of longitudinal latent growth analysis (e.g., growth mixture modelling, latent class growth analysis, group trajectory models); demonstrate the similarities based and differences of these models with other methods commonly used for the analysis of longitudinal data with repeated measures; explain how these methods can help address methodological challenges that arise in rheumatological research; and provide exemplar manuscripts from related fields to demonstrate use of these methods and interpretation of their results. During this session, we will introduce the most popular longitudinal latent growth models (LGM) approaches in current use. Given the rapid development of these methods, it can often be a significant challenge for clinical researchers to be aware of such ongoing developments and to apply them appropriately to their own data. Moreover, within the family of LGM models the same model may be termed differently, which often creates confusion in reading the literature. A number of important differences exist across these various approaches, and the selection of the optimal method for a given dataset is not always apparent. The aim of this session is to address such possible confusion experienced by researchers.
Speaker: Jamie Collins, PhD – Brigham and Women's Hospital
Speaker: Liubov Arbeeva, MSc – University of North Carolina, Chapel Hill
Speaker: Louise Thoma, PhD, DPT – University of North Carolina