Experience & Expertise
Dr. Calistro has extensive knowledge and work experience across numerous statistical domains, including hypothesis testing, data visualization, linear and generalized linear modeling, structural equation modeling, linear mixed modeling, generalized linear mixed modeling, factor analysis, psychometrics, Bayesian statistics, non-parametric statistics, survival analysis, robust statistics, time series analysis, and machine learning.
His psychometric expertise includes classical test theory and item response theory. His machine learning experience includes supervised, unsupervised, and reinforcement learning models. Dr. Calistro also has quantitative research expertise in randomized controlled trials, quasi-experimental design, meta-analysis, correlational research, survey research, and secondary data analysis.
Dr. Calistro has worked as a statistician for multiple federally funded grants, including Institutional Resilience and Expanded Postsecondary Opportunity, the National Institute on Disability, Independent Living, and Rehabilitation Research, and Helping Evidence-Based Advocates with Responsive Training grants. He has also completed over 100 statistical consultation projects.