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Author Archives: Jerry Reiter

TCRN publishes paper in JOS on theory of partially synthetic data

TCRN investigators have authored a paper to appear in the Journal of Official Statistics showing that analytically-valid, partially synthetic data need not be generated from posterior predictive distributions.  This simplifies the generation of partially synthetic data.

 

Jerry Reiter to give plenary talk at Pol Meth conference

Jerry Reiter will give a plenary talk at the Political Methodology conference on July 20.  The talk is titled, “The multiple adaptations of multiple imputation.”

TCRN publishes paper in JASA on estimating disclosure risks

The TCRN has made some methodological advances related to assessing disclosure risk and imputing missing data.  TCRN investigators Daniel Manrique-Vallier and Jerry Reiter developed a way to estimate whether records that are unique in a sample are in fact unique in a population.  Their approach, based on grade of membership models, outperforms state-of-the-art methods based on log-linear modeling.  Manrique-Vallier and Reiter are developing other approaches that are computationally fast and can handle structural zeros, the latter of which has not been dealt with satisfactorily in the disclosure risk estimation literature.  Check the White Papers section of this site soon for more details.

TCRN no longer active

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