Dr. Douglas Gunzler is a tenured Associate Professor of Medicine and Population and Quantitative Health Sciences in the Population Health Research Institute at the Center for Health Care Research and Policy, MetroHealth at Case Western Reserve University. He is a Biostatistician with specialties in structural equation modeling (SEM) and longitudinal data analysis. His research interests lie in the areas of mediation analysis, factor analysis, mixture modeling, psychometrics, age-period-cohort analysis and their application to both clinical trials and observational studies in health and medicine. In his research, he is using SEM for analysis of overlapping symptoms in co-occurring conditions. Dr. Gunzler received his PhD from the Department of Biostatistics & Computational Biology at the University of Rochester in 2011.

Dr. Adam Perzynski is a tenured Associate Professor of Medicine and Sociology in the Center for Health Care Research and Policy at MetroHealth and Case Western Reserve University. He is also the Founding Director of the Patient Centered Media Lab. His doctoral degree is in sociology and his current research interests include: novel strategies to eliminate health disparities, outcomes measurement over the life course and research methods. His methodologic expertise spans the continuum from focus groups and ethnography to psychometrics and structural equation modeling. His publications span many disciplines and stand out against the backdrop of a career long effort to infuse the study of biomedical scientific problems with the knowledge, theories and methods of social science.

Dr. Adam C. Carle is a clinically and quantitatively trained investigator. He is nationally recognized as an expert in pediatric patient reported outcomes and measurement. He uses structural equation models (SEM), multilevel models (MLM), and contemporary test theory (e.g., item response theory: IRT) to advance the methodological science used to measure health and health related outcomes from the family and child's perspective, investigate the correlates of children and their families' well-being, and investigate and eliminate health disparities. Additionally, his work seeks to better understand individual and contextual variables' influences on health and health disparities at individual, local, system, state, and national levels. He is a PI, Co-PI, or Co-I on numerous Federal grants and has served as a reviewer for Federal granting agencies and national foundations. He has published over 80 peer reviewed manuscripts. Most important, he thinks his family is amazing (including the dogs and sheep).

Part I Introduction to Concepts and Principles of Structural Equation Modeling for Health and Medical Research

1. Introduction and Brief History of Structural Equation Modeling for Health and Medical Research
2. Vocabulary, Concepts and Usages of Structural Equation Modeling

Part II Theory of Structural Equation Modeling

3 The Form of Structural Equation Models
4 Model Estimation and Evaluation
5 Model Identifiability and Equivalence

Part III Applications and Examples of Structural Equation Modeling for Health and Medical Research

6 Choosing Among Competing Specifications
7 Measurement Models for Patient-Reported Outcomes and Other Health-related Outcomes
8 Exploratory Factor Analysis
9 Mediation and Moderation
10 Measurement Bias, Multiple Indicator Multiple Cause Modeling and Multiple Group Modeling
11 Latent Class Analysis
12 Latent Profile Analysis
13 Structural Equation Modeling with Longitudinal Data
14 Growth Mixture Modeling
15 Special Topics