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Paul Wesley Scott
PhD
Assistant Professor
Health & Community Systems
Profile
Dr. Scott is a research methodologist specialized in psychometrics and statistical analyses in the behavioral, cognitive, and social sciences. His three primary methodological topics of interest are: (1) Causal Inference; (2) Dynamic Panel & Intensive Longitudinal Data; and, (3) Clustering & Categorical Latent Variables. In applied research, he has worked with a number of research teams across a variety of substantive areas. Within the school he works most closely with the Research HUBS for Sleep & Circadian Sciences, Health Services & Policy, and Nursing Education & Scholarship. He is affiliated with the T32 training faculty for excellence in digital health.
As a Faculty Statistician, Dr. Scott provides quantitative research support to faculty and doctoral students in a broad range of topics, thinking through strategies for data collection, management, analysis, and interpretation of results. These experiences have provided familiarity working with diverse data sources and structures across many modeling frameworks.
Scholarly Emphasis
Dr. Scott's research focuses on Longitudinal Data Analysis; Causal Inference; Latent Variable Modeling; Bayesian Inference; Data Science; and Foundations of Statistical Reasoning.
Teaching
Dr. Scott currently teaches NUR 0088: Basic Statistics for EBP,NUR 2011: Applied Statistics for EBP, NUR 3112: Applied Parametric and Non-Parametric Statistics 1, NUR 3113: Applied Parametric and Non-Parametric Statistics 2, NUR 3114: Applied Regression Analysis, and NUR 3288: Research Measurement.
Service
Dr. Scott is a member of the American Statistical Association and the Psychometric Society. He has contributed methodological review on several applied research journals, reviewer for Structural Equation Modeling: A Multidisciplinary Journal, and served as a subject matter expert peer reviewer for a PCORI-funded research report. He is also a Steward and Griever for USW Local 1088-04.