Please find information below on an upcoming webinar, sponsored by the Mental Health Statistics Section.
Title: Recent Advances in Modeling Short and Long Longitudinal Data
Presenter: Dr. Bengt Muthen, University of California-Los Angeles
Date and Time: Tuesday, May 24, 12:00 p.m. – 2:00 p.m. Eastern time
Sponsor: Mental Health Statistics Section
Registration Deadline: Tuesday, May 24, at 11:30 a.m. Eastern time
Description:
This talk discusses analysis of repeated measures for binary, ordered polytomous, continuous, and semi-continuous outcomes frequently seen in mental health research. The first part of the talk considers panel data with a small number of time points (5-10). A random effects two-part ordinal model is introduced for longitudinal analysis of treatment effects and random intercept cross-lagged modeling (RI-CLPM). The second part of the talk considers intensive longitudinal data with many time points (50-100). Two-level time series analysis (dynamic structural equation modeling; DSEM) is used for modeling of daily cycles by sine-cosine curves as well as two-part modeling of semi-continuous outcomes that have strong floor effects. Examples are drawn from a randomized trial of treatments of alcohol dependence, a study of suicidal ideation and substance abuse, and studies of negative affect and at-risk mood profiles related to depression in adolescents.
About the Instructor:
Bengt Muthén obtained his Ph.D. in Statistics at the University of Uppsala, Sweden and is Professor Emeritus at UCLA and a co-developer of the Mplus software. He was the 1988-89 President of the Psychometric Society, the 2011 recipient of the Psychometric Society's Lifetime Achievement Award, and the 2017 recipient of the Sells Award for Outstanding Career Contributions to Multivariate Experimental Psychology. He has written extensively on latent variable modeling.
Registration:
Members of the Mental Health Statistics Section: $20
ASA Members: $30
Student ASA Member: $25
Nonmembers: $45
Each registration is allowed one connection to the webinar. Multiple persons are encouraged to view each registered connection (for example, by projecting the webinar in a conference room)
Registration Link: https://www.amstat.org/education/web-based-lectures
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Adam Ciarleglio
Assistant Professor
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