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Methodology and Measurement in the Behavioral and Social Sciences Exploratory/Development Grant (R21)

The purpose of this Funding Opportunity Announcement (FOA) is to invite qualified researchers to submit grant applications aimed at improving and developing methodology in the behavioral and social sciences through innovations in research design, measurement, data collection and data analysis techniques.

Deadline: 

Monday, June 17, 2019

Methodology and Measurement in the Behavioral and Social Sciences Research Grant (R01)

The purpose of this Funding Opportunity Announcement (FOA) is to invite qualified researchers to submit grant applications aimed at improving and developing methodology in the behavioral and social sciences through innovations in research design, measurement, data collection and data analysis techniques.

Deadline: 

Wednesday, June 5, 2019

Stan, Scalable Software for Bayesian Modeling

This award is to design, code, document, test, dissememinate, and maintain Stan, an extensible open-source software framework and compiler for efficient and scalable Bayesian statistical modeling. Stan is an extensible, open-source, cross-platform software framework for developing Bayesian statistical models. The first step in Bayesian modeling is setting up a full probability model for all quantities of interest. Stan facilitates this process by providing an expressive and extensible domain-specific programming language for specifying probabilistic models.

Solving Difficult Bayesian Computation Problems in Education Research with Stan

Some statistical models used in education research are complex. This complexity arises in part because the data structures that underlie these statistical models involve multiple nested (i.e., cross-classified multilevel models) and non-nested groupings (i.e., partially-nested designs). Another source of complexity in these models results from the fact that key variables, such as student achievement, can be measured only indirectly and are represented in the model by latent variables.

AERA-MET Dissertation Fellowship Program

To support dissertation research that uses the Measures of Effective Teaching Longitudinal Database.

Deadline: 

Monday, May 16, 2016

Minority Dissertation Fellowship Program in Education Research

To support dissertation research on U.S. education issues. Applicants must be members of racial and ethnic groups historically underrepresented in higher education.

Deadline: 

Thursday, November 1, 2018

Dissertation Grants

To support dissertation research related to U.S. education issues.

Deadline: 

Wednesday, September 25, 2019

Research Grants

To support grants on U.S. education issues.

Deadline: 

Wednesday, May 15, 2019

Using Multilevel Regression and Poststratification to Measure and Study Dynamic Public Opinion

This research project will develop techniques for using national survey data to estimate dynamic measures of public opinion across a variety of types of subnational units such as states, congressional districts, and state legislative districts. These techniques will allow researchers to generate accurate estimates of public opinion over time by fine-grained demographic-geographic-temporal subgroups. National surveys are designed to give good estimates of national public opinion at a particular point in time.

Collaborative Research: Multilevel Regression and Poststratification: A Unified Framework for Survey Weighted Inference

This research project will develop a unified framework for survey weighting through novel modifications of multilevel regression and poststratification (MRP) to incorporate design-based information into modeling. Real-life survey data often are unrepresentative due to selection bias and nonresponse. Existing methods for adjusting for known differences between the sample and population from which the sample is drawn have some advantages but also practical limitations.

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