Andrew Gelman

Associated IES Content

Grant

Solving Difficult Bayesian Computation Problems in Education Research Using STAN

Federal funding program:
Statistical and Research Methodology in Education
Award number:
R305D140059
Grant

Efficient and Flexible Tools for Complex Multilevel and Latent Variable Modeling in Education Research

The project team developed improved tools for fitting statistical models in complex settings, specifically hierarchical Bayesian models for handling multilevel data including nested and non-nested groupings, latent variables, and large numbers of parameters.
Federal funding program:
Statistical and Research Methodology in Education
Award number:
R305D190048

FY2012 - FY2014

FY2012 - FY2014 Statistics and Modeling Peer Review Panel
Grant

NYU/Columbia Postdoctoral Training Program

This training program prepared four researchers to (a) develop statistical methods required to meet future education research challenges and (b) teach other researchers how to use more advanced quantitative methods.
Federal funding program:
Research Training Programs in the Education Sciences
Award number:
R305B120017
Grant

Practical Tools for Multilevel Hierarchical Modeling in Education Research

In this project, the researchers developed and tested new approaches to support applied researchers' use of Bayesian modal estimation (also called maximum a posteriori estimation) for multilevel models. The goal of this methodological innovation was to make it easier for applied researchers to avoid nonsensical results when they use multilevel models.
Federal funding program:
Statistical and Research Methodology in Education
Award number:
R305D100017

FY2011 IES Peer Reviewers

FY2011 IES Research Peer Review Panel

FY2011 - FY2013

FY2011 - FY2013 Statistics and Modeling Peer Review Panel
Grant

Practical Solutions for Missing Data and Imputation

Missing data are ubiquitous in education research studies. The literature discusses the shortcoming of simple missing data approaches such as complete case analysis and inclusion of indicators for missing data; however, the use of these practices remains widespread. Multiple imputation is becoming an increasingly widely used approach to handling missing data but there are outstanding research questions regarding the most reliable methods for implementing it and when it is worthwhile to inves...
Federal funding program:
Statistical and Research Methodology in Education
Award number:
R305D090006

FY2010 - FY2012

FY2010 - FY2012 Statistics and Modeling Peer Review Panel

FY2009 IES Peer Reviewers

FY2009 IES Research Peer Review Panel