Project Grant 2316353
- 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 $148,606 Project Grant award from the National Science Foundation's Social, Behavioral, and Economic Sciences (CFDA 47.075) program to William Marsh Rice University supports the development of new statistical theory, methodology, algorithms, and software to produce more robust survey estimates. The research addresses the widespread problem of survey respondent "satisficing," where respondents provide low-effort responses without sufficiently considering survey questions. The...
- The National Science Foundation (NSF) awarded a $350,796 Project Grant under the Mathematical and Physical Sciences program (CFDA 47.049) to South Dakota State University (SDSU) to develop statistical methods for detecting and characterizing latent subpopulations within large, complex datasets. The research aims to create flexible, stable, and trustworthy models for "few-shot" or "one-shot" learning problems, where there are only a few examples in each data category. The...
- This $423,340 National Science Foundation project grant supports research at the University of Southern California to develop statistical models for selecting optimal populations. The goal is to establish reliable decision-making rules for determining which of multiple approaches or populations provides the best solution to a given problem. The three-year award under the NSF Engineering program (CFDA 47.041) will investigate methods for identifying the population with the largest mean based on...
- 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 $349,993 federal Project Grant award from the National Science Foundation's (NSF) Social, Behavioral, and Economic Sciences (CFDA 47.075) program will advance the methodology and practical implementation of adaptive experiments. The 3-year project, which begins on September 1, 2024, will develop new statistical methods for sample size calculations and optimal treatment assignment in adaptive settings, establish a comprehensive framework to guide applied researchers in designing adaptive...
- The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $200,000 Project Grant to The University Corporation, a non-profit organization located in Northridge, CA. The grant, funded under the NSF's Mathematical and Physical Sciences program (CFDA 47.049), focuses on developing new statistical modeling and data resampling methods to address challenges posed by incomplete, missing, and fragmented observations in large datasets. Key objectives include: Advancing...
- 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 $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 $375,000 Project Grant award from the National Science Foundation's Social, Behavioral, and Economic Sciences (CFDA 47.075) program supports research to advance Bayesian inference methods for the analysis of complex human data. The project, conducted by Rensselaer Polytechnic Institute, will develop an efficient amortized Bayesian inference framework that enables researchers across the social and behavioral sciences to quickly fit, criticize, and adapt complex computational models. The...
The National Science Foundation (NSF) Social, Behavioral, and Economic Sciences program awarded a $214,625 Project Grant to the San Diego State University Research Foundation (SDSURF) to develop new model-based estimators for improving the precision of population parameter estimates in small area survey sampling. The project will create clustered coefficient regression models that can better handle heterogeneous relationships between survey variables and auxiliary data, compared to traditional homogenous models. The new estimators will be applied to national surveys like the American Community Survey, with results incorporated into a survey sampling course. The project will also produce publicly available R software packages. Both undergraduate and graduate students will be involved in the research.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $214.6k | 8/14/23 |