August 29, 2016 •Austin Lasseter, Ph.D.
On July 31, 2016, I presented a research paper at the Survey Research Methods Section of the JSM Conference in Chicago. Mine was one of six contributed papers on the topic of Raking, Post-Stratification, and Calibration Methods in survey research.
Together with my co-author Jonathan Phelan of the American Institutes for Research (AIR), I discussed:
Our paper demonstrated how raking adjustments to sampling weights could substantially reduce bias due to non-coverage when extrapolating the High School Longitudinal Study (HSLS) follow-up results to all high school seniors in the nation in 2013.
The study used data from three datasets of the National Center of Education Statistics (NCES): the HSLS, the National Assessment of Educational Progress (NAEP), and the Common Core of Data (CCD). Our research paper was written during my time at AIR as part of a contract with the National Center for Education Statistics (NCES).
During the same session there were several other authors presenting papers on topics related to ours. A few highlights from our session included the following:
Thanks to Summit for supporting my participation at this conference! I look forward to continuing the dialogue.
In early August 2016, I presented at the National Academy of Education (NAEd) “Big Data: Balancing Research Needs and Student Privacy” workshop. You can read my blog post about NAEd here.