Our research aims to establish scientific evidence that is meaningful at the individual level and scalable to evidence-based practice. We ground our work in the estimand framework outlined in the International Council for Harmonisation E9(R1) addendum. This framework promotes clear alignment among study objectives, design, conduct, and statistical analysis. In addition, we develop methods that clarify what researchers estimate, how they estimate it, and how evidence accumulates across studies.

We develop methods that support rigorous causal inference from individual-level data. Our work centers on defining causal estimands that reflect the questions stakeholders seek to answer, formalizing counterfactual reasoning, and designing statistical procedures that yield reliable estimates of intervention effects. The aim is to distinguish signal from noise—to ensure that observed changes in outcomes can be attributed to the intervention rather than to chance or uncontrolled influences. Central to this effort is the explicit articulation of assumptions that underlie scientific conclusions.

Effect sizes translate intervention evidence into quantities that can be compared, interpreted, and synthesized. They must be causally meaningful, statistically sound, and interpretable to those who rely on them—researchers, practitioners, families, and policy makers. We develop effect size measures that are comparable across studies, meaningful for the intervention question at hand, and accessible in interpretation. We also seek to connect effect size measures across research designs, enabling researchers to integrate and interpret evidence from SCEDs, randomized trials, and other intervention studies within a broader evidence base.

Evidence at the level of the individual is only the beginning. To inform broader practice, researchers must bring evidence together with care. We develop methods for synthesizing results across SCED studies to estimate population-level treatment effects while preserving meaningful variation across individuals. This work connects individual findings to general conclusions and provides empirical benchmarks that help interpret the magnitude of intervention effects in context.

A central part of our mission is to bridge research and practice. We develop tools, resources, and guidance that make rigorous methods accessible in real-world settings, enabling practitioners and applied researchers to generate and use high-quality evidence.