We are committed to advancing methodology related to applied psychometrics in the areas of instrument development, analysis and evaluation. Our team integrates perspectives from disciplines such as statistics, psychology, and education to build a strong foundation for improving the field of psychometrics. This foundation facilitates our ability to develop creative solutions to applied psychometric questions for researchers across a variety of academic disciplines.
Our expertise extends to both quantitative and qualitative methodologies, and we often collaborate with interdisciplinary and mixed methods projects. As such, we’re especially interested in using mixed methods for educational research—including instrument development studies, program evaluation and intervention designs.
We are dedicated to advancing research methods related to the prevention of social, academic, and physical and mental health problems, as well as risky behaviors. By integrating methodological perspectives from a variety of disciplines—including statistics, psychology, education, human development, and public heath—we address research questions related to prevention science. By collaborating with prevention scientists, we create foundations for continued innovation and excellence in prevention science.
Our research focus includes program evaluation within educational settings from preschool through early career. We conduct methodological and applied research studies to enhance our understanding of education evaluation in accountability and assessment, early childhood education, and school improvement, effectiveness and reform. Our commitment is to translate evaluation theory to practice.
Statistics & Modeling
We are dedicated to the development, improvement, evaluation, and novel application of quantitative methods, with the end goal of fostering methodologically sound research in the social, behavioral and education sciences. Our combined backgrounds in statistics, quantitative methods, psychology, and education allow us to conduct research on quantitative methods that is statistically rigorous and innovative, and at the same time maximally relevant to real-world applications.