Home » Miscellaneous » TCRN publishes paper on multiple imputation in large scale categorical databases

TCRN publishes paper on multiple imputation in large scale categorical databases

TCRN researcher Jerry Reiter and former graduate student Yajuan Si have published a paper on the use of nonparametric Bayesian methods for multiple imputation of missing data in large-scale categorical databases.  They applied the methods to impute background characteristics in the Trends in International Mathematics and Statistics Study.  The paper will appear in the Journal of Educational and Behavioral Statistics.


Leave a comment

Your email address will not be published. Required fields are marked *

TCRN no longer active

The NSF award that supported the TCRN ended on September 30, 2018.  This site is maintained for archival purposes.