Project Grant 2150573
Award Date
9/1/22
Completion Date
8/31/25
Dollars Obligated
$420K
Federal Agency
Division of Behavioral and Cognitive Sciences
Federal Grant Program
47.075
Assistance Type
Project Grant
Place of Performance
NEWCOMB HALL, VA 22904, USA
Similar Awards
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...
The National Science Foundation awarded a $360,000 project grant to the University of Alabama under the Social, Behavioral, and Economic Sciences program (CFDA 47.075) for the period of June 1, 2022 through May 31, 2025. The grant will support research to advance the development and application of cognitive diagnosis models (CDMs), which are psychometric tools used to infer unobserved psychological attributes from responses to test or survey items. Specifically, the university will create a...
The University of Georgia Research Foundation, Inc. received a $300,000 Project Grant award from the National Science Foundation Social, Behavioral, and Economic Sciences program (CFDA 47.075) to develop new statistical methods and software for item response theory model calibration applicable to computerized adaptive testing in small-scale assessments. Key products to be delivered under the three-year award period include dimension reduction methods for item response theory models 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 $279,983 National Science Foundation project grant supports research at Brown University to develop hybrid statistical and econometric modeling methods. Funded under the NSF Social, Behavioral, and Economic Sciences program, the three-year award beginning August 2022 aims to advance modeling approaches that account for imperfect data measurement and the reality that models approximate rather than perfectly represent the world. The research will modify method-of-moments techniques to...
This $149,961 Project Grant from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049) will support research into optimal subdata selection methods using mixture-of-experts models to account for heterogeneity in large datasets. Specifically, the awardee, George Mason University, will develop and study subdata selection frameworks and methods based on clusterwise linear regression and logistic-normal mixture models. Information-based optimal subdata...
This National Science Foundation (NSF) Social, Behavioral, and Economic Sciences (CFDA 47.075) Project Grant award of $300,000 to Florida State University (FSU) supports the development of a new class of latent variable models for network data. The research aims to create models that can capture essential characteristics observed in network data from various disciplines, including the social and life sciences. Key activities include integrating and extending existing approaches to modeling...
This two-year, $229,951 Project Grant from the National Science Foundation's Social, Behavioral, and Economic Sciences program aims to advance statistical and psychometric theory for Cognitive Diagnosis Models. Funded from September 2021 through August 2023, the University of Nevada, Reno will develop Bayesian methods for inferring attribute hierarchy structures within CDMs. Algorithms will estimate underlying skill hierarchies from data and allow statistical inference of attribute...
This federal Project Grant award of $249,999.00 from the National Science Foundation (NSF) Social, Behavioral, and Economic Sciences (CFDA 47.075) program aims to enhance policy decisions based on statistical models that are incorrectly specified but closely fitting. The research project will develop new equation-by-equation maximum likelihood estimation methods for structural equation models involving latent variables to provide more accurate inferences for correctly specified equations...
This National Science Foundation (NSF) Project Grant under the Social, Behavioral, and Economic Sciences (CFDA 47.075) program will provide $750,000 to The Washington University to test three competing conceptual models for how person and situation factors influence human behavior. The research will develop more personalized assessment methods to determine when person vs. situation factors are more important in predicting behavior for different individuals. This multi-year project will...