Dana Scott Mills, PhD is an applied statistician and research methodologist with over two decades of experience in quantitative analysis, mixed methods, and program evaluation across education, health, and community-based research. He has served as principal investigator or co-investigator on numerous federally and institutionally funded studies, including NIH-funded research. Dr. Mills has extensive experience consulting with faculty and external organizations, helping teams design rigorous studies, select appropriate analytic strategies, and translate complex data into meaningful, actionable results.
Statistical Interests:
Applied quantitative methods, advanced modeling of complex and hierarchical data, longitudinal and multilevel analysis, causal inference, and program evaluation in educational, health, and community-based research.
Statistical Methods:
Structural Equation Modeling (SEM), including latent variable and measurement models, latent growth curve and longitudinal modeling, multivariate/predictive regression modeling, experimental and quasi-experimental analysis (e.g., ANCOVA, propensity-based approaches).
