Taylor Lewis
Dr. Taylor Lewis has broad expertise in the statistics behind modern survey research methods, including sample design, responsive and adaptive survey design, weighting and imputation, replication variance estimation procedures and disclosure avoidance techniques used in the release of survey microdata. He works full-time as a Senior Research Statistician for RTI International. He is also an adjunct professor for the George Mason University Department of Statistics.
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Areas of Interest
Adjuncts and AffiliatesSampling Design and Analysis; Survey Methodology; Weighting and Imputation
PhD, Survey Methodology, 2014
University of Maryland
MS, Survey Methodology, 2009
University of Maryland
BS, Statistics, 2005
Virginia Tech
EPIB660 Analysis of National Health Survey Data
Lewis, T. (2016). Complex Survey Data Analysis with SAS®. Chapman and Hall/CRC Press. https://www.crcpress.com/Complex-Survey-Data-Analysis-with-SAS/Lewis/9781498776776.
Lewis, T., Gorsak, M., and Yount, N. (2019). “An Automated Refusal Conversion Strategy for Web Surveys.” Field Methods, 31(4), pp. 309 – 327.
Lewis, T. (2017). “Univariate Tests for Phase Capacity: Tools for Identifying When to Modify a Survey’s Data Collection Protocol.” Journal of Official Statistics, 33(3), pp. 601 – 624.
Lewis, T. (2019). “Multivariate Tests for Phase Capacity.” Survey Research Methods, 13(2), pp. 153 – 165.
Lewis, T. (2017). “Temporal Perspectives of Nonresponse During a Survey Design Phase.” methods, data, analyses, 11(2), pp. 189 – 206.
Lewis, T., Goldberg, E., Schenker, N., Beresovsky, V., Schappert, S., Decker, S., Sonnenfeld, N., and Shimizu, I. (2014). “The Relative Impacts of Design Effects and Multiple Imputation on Variance Estimates: A Case Study with the 2008 National Ambulatory Medical Care Survey.” Journal of Official Statistics, 30(1), pp. 147 – 161.