This National Science Foundation project grant of $281,469 will fund research at the University of Colorado Denver from August 2022 through July 2025 to advance causal inference methods for heterogeneous data fusion. Specifically, the award will support developing new approaches to empirically estimate associations and perform causal inference when individual-level data cannot be obtained due to privacy or logistical constraints. The research aims to extend statistical methodologies to accommodate real-world scenarios across multiple disciplines, including medicine, the social sciences, and public health. Key deliverables include new theoretical underpinnings in areas like statistical theory and causal inference. Graduate students will receive training, and software and curricula in causal inference will be created. This work falls under the NSF's Social, Behavioral, and Economic Sciences program (CFDA 47.075), which supports basic research and education to contribute to the scientific strength and welfare of the nation.