Behavioral science, psychometrics, and AI-driven insights shaping research and practice.
PrimeStata’s research portfolio bridges academic rigor with applied innovation — spanning psychometric validation, organizational design, and AI-assisted decision systems. Each publication integrates statistical precision with psychological theory and real-world impact.
Steiner, R. N. (in prep / under review). University of Akron Dissertation.
Introduces the IIBES framework — a multidimensional model of behavioral engagement across independent and interdependent domains. Employs factor analysis and multilevel modeling to capture team-based and individual engagement dynamics.
🧠 Contributes to measurement theory and team performance science.
Steiner, R. N. (2023). Psychreg Journal of Psychology, 7(2), 1-15.
Theorizes a dual-pathway motivation model integrating autonomy (independent) and collaboration (interdependent) drives. Explores implications for engagement, performance, and leadership assessment.
📈 Bridges motivation theory with applied organizational design.
Read Publication →Steiner, R. N. (2021). PrimeStata Research Working Paper.
Applies psychometric modeling and predictive analytics to organizational assessment contexts. Examines construct alignment, reliability trade-offs, and ethical interpretability in data-driven HR and talent systems.
📊 Integrates psychometrics with data science for evidence-based practice.
Steiner, R. N. (2025). PrimeStata White Paper Series.
Argues for hybrid architectures where human judgment and AI inference co-govern decisions. Explores transparency, fairness, and the augmentation of psychological safety through algorithmic insight.
🤖 Defines principles for equitable Human + AI collaboration.
PrimeStata welcomes academic and applied collaborations across behavioral science, data analytics, and AI-ethics domains. For manuscript requests, data partnerships, or co-authorship opportunities, reach out directly.