Project Grant 2242820

Award Date 9/1/23
Completion Date 8/31/26
Dollars Obligated $375K
Federal Grant Program
47.075
Assistance Type
Project Grant
Place of Performance
Ames, IA 50011, USA
Similar Awards
This National Science Foundation (NSF) award, made under the Mathematical and Physical Sciences Program (CFDA 47.049), supports the development of new methods for aggregating information from multiple datasets in three key data integration problems: meta-analysis, model fusion, and transfer learning. The $172,186 project, awarded to North Carolina State University, aims to create intuitive, principled, and robust approaches to extract insights from large datasets across medical, economic, and...
This three-year, $674,542 National Science Foundation project grant supports research at the University of California Santa Cruz to develop Bayesian statistical and machine learning methods for analyzing complex survey data from the federal statistical system. The grant falls under the NSF's Social, Behavioral, and Economic Sciences program (CFDA 47.075), which promotes basic research and education in these fields. Specifically, the investigators will extend existing models using data...
This $226,874 Project Grant awarded by the National Science Foundation (NSF) Social, Behavioral, and Economic Sciences (SBE) program (CFDA 47.075) will fund research to develop new statistical tools for modeling and analyzing dependent data. The project, to be conducted by Cornell University, will focus on advancing methods for handling data dependencies in areas such as local elections, inflation modeling, spatial patterns, and environmental monitoring data. The research aims to provide...
This Project Grant from the National Science Foundation's National Center for Science and Engineering Statistics will fund the development of Bayesian statistical and machine learning methodologies tailored for complex survey and census data. Awarded $743,050 under the Social, Behavioral, and Economic Sciences program, the grant will support research at the University of Missouri from September 2022 through August 2025. The research aims to advance computational efficiency and expand...
This $289,999 National Science Foundation project grant, awarded under the Mathematical and Physical Sciences program (CFDA 47.049), will fund the development of improved statistical methods, algorithms, and theory for estimation and inference with high-dimensional data at Rutgers, The State University from July 2022 through June 2025. Key products include new statistical methods for regularized estimation, de-biased statistical inference including confidence intervals and regions, and empirical...
This $233,955 Project Grant award from the National Science Foundation's (NSF) Social, Behavioral, and Economic Sciences (CFDA 47.075) program will support a research project at The Washington University in St. Louis to develop improved methods for probabilistic data integration and record linkage without the use of unique identifiers. The central objectives are to create computationally efficient and accurate techniques for merging large datasets from multiple sources, which is a critical...
This National Science Foundation (NSF) Social, Behavioral, and Economic Sciences (SBE) Program (CFDA 47.075) Project Grant award to Iowa State University of Science and Technology provides $305,912 from August 1, 2024 to July 31, 2027 to examine how accurately U.S. adults interpret different types of data visualizations. The researchers will implement an online survey of 2,000 respondents to measure their understanding and interpretation of various data visualization designs, such as bar and...
This Project Grant award of $194,675 from the National Science Foundation's (NSF) Social, Behavioral, and Economic Sciences (CFDA 47.075) program supports research to develop new econometric and statistical methods that allow researchers to draw valid conclusions from complex data in a variety of social, behavioral, and medical science settings. The key products and services to be delivered include: Developing a generally applicable reparameterization procedure for informative...
This National Science Foundation project grant of $400,000 awarded on August 15, 2022 through July 31, 2025 under the Social, Behavioral, and Economic Sciences program (CFDA 47.075) will fund research at Duke University to advance statistical and computational methods for releasing high-quality synthetic data as public use files. The research aims to develop novel techniques to improve disclosure risk assessment, quality verification for data analysts, and population generalizability when...
The National Science Foundation (NSF) awarded a $237,438 Project Grant to Purdue University under the Social, Behavioral, and Economic Sciences grant program (CFDA 47.075) to advance statistical inference on dynamic systems. The 3-year project will leverage deep learning and statistical modeling to enhance the efficiency, accuracy, and interpretability of time-series analysis across various domains. The research will introduce a new neural inference framework for estimating and inferring dynamic...

This federal Project Grant award from the National Science Foundation's (NSF) Social, Behavioral, and Economic Sciences program (CFDA 47.075) provides $375,000.00 to Iowa State University of Science and Technology to develop statistical and machine learning tools for data integration and data fusion. The project aims to enhance the analysis of complex survey data with big data sources, as well as improve scientific conclusions drawn from multiple datasets. Key activities include research on mass imputation using machine learning, propensity score weighting, high-dimensional calibration weighting, and optimal estimation and sampling design for data fusion. The project results will be disseminated through publications, presentations, training, and software. No sub-awards are planned as part of this 3-year grant, which commenced on Sep 1, 2023.

Generated 5/14/24, 1:24 AM