Grant Submissions Link
March 25, 2019 @ 8:00 am - 8:30 am
If you have any new grant submissions coming up, please fill out the form here:
March 25, 2019 @ 8:45 am - 9:45 am
Douglas Gunzler, PhD
Center for Health Care Research & Policy
MetroHealth Medical Center
Case Western Reserve University
Latent Variable Mixture Modeling for Cross-Sectional Data in Health and Medicine
In this seminar, I will introduce latent variable mixture modeling techniques for cross-sectional data. In particular, latent class and latent profile analysis are useful multivariate techniques for describing subgroups in study samples based on selected variables. These techniques are probabilistic in nature, where classes are described based on empirical evidence and interpretability. In this seminar, I will discuss how to apply these techniques using complex clinical research data. I will discuss assumptions made in using latent profile analysis (LPA) on 200 clinical trial participants with a serious mental illness and diabetes. LPA in this sample explored differentiation between subgroups that were characterized on the basis of selected dimensions within a biopsychosocial framework. The study team identified two trivial subgroups (characterized by high and low scores on psychosocial measures) using a standard application of LPA. In making additional assumptions in line with clinical theory, we identified five meaningful subgroups. We also evaluated a secondary auxiliary model to describe relationships between latent classes and other clinical factors.
Dr. Gunzler is an Assistant Professor of Medicine and Population and Quantitative Health Sciences at the Center for Health Care Research and Policy, Case Western Reserve University. His research has focused on structural equation modeling and longitudinal analysis, emphasizing mediation analysis and latent variable mixture modeling, psychometrics, multi-level modeling, and age-period-cohort analysis. He has applied these methods to many clinical trials and observational studies, especially multiple sclerosis (MS) and mental health studies. He was a KL2 research scholar within the NIH-funded Clinical and Translational Science Collaborative (CTSC) of Cleveland with a focus on looking at depression issues in MS patients. He is currently continuing his KL2 research in using electronic health records for looking at depression issues in hemodialysis patients as well as developing risk prediction tools for adults with type 2 diabetes and persons with MS. Dr. Gunzler received his PhD degree in Statistics from the University of Rochester in 2011.
PQHS Faculty Meeting
April 4, 2019 @ 12:00 pm - 1:00 pm