- Publications across various fields: Bayesian analyses, dominance analysis (linear regression), open science, personality, knowledge and expertise, multitasking, AI and machine learning, meta-analysis, measure development, and other methods papers.
- Involvement in National Academies Reports.
Research Experience
- The research team focuses on defining and measuring individual and team performance in employment, military, and academic settings.
- Examines key correlates of performance such as promotion, certification, attrition, and satisfaction.
- Investigates individual differences that contribute to performance, including knowledge, skill, and motivation.
- Studies school-to-work transitions, with a focus on subgroups like STEM, gender, racial/ethnic minority, and first-generation college students.
- Looks into the legal implications and applications of personnel selection practices.
- Develops and improves selection and admissions tests, metrics, and systems.
- Statistically models the psychometric reliability, validity, and structure of psychological tests.
- Utilizes, critiques, and extends statistical methods used in organizational research, including big data and machine learning, meta-analysis, CFA/SEM, IRT, multilevel models, Bayesian analysis, adverse impact analysis, and other methods.
Background
Research interests include employee performance and academic success, workforce readiness and personnel selection, developing psychological tests, and big data and modern analytics for organizations and colleges.
Miscellany
Teaches statistical methodologies in graduate seminars, short courses, and workshops; advises graduate students, academic and practitioner colleagues, and various stakeholders on their statistical analyses, particularly those relevant to organizational research and practice.