As senior vice president, Edward (Ed) directs the Statistics & Data Science department for NORC at the University of Chicago. He has over 35 years of statistical consulting experience, which includes: area probability sampling, tax compliance sampling, utilizing administrative records, utilizing nonprobability samples, Bayesian methods, evaluation methods, geographic information systems, visualization, data mining, record linkage, statistical matching, and performance measurement comparisons for determining parity.
Ed is the project director for record linkage projects with the National Center for Health Statistics. (NCHS). NCHS houses unique national data resources and expertise, including (1) the National Hospital Care Survey (NHCS), which provides unique statistics on health and health care utilization based on patient hospital and emergency department (ED) visits, medical claims records and Electronic Health Records (EHRs), as well as information on provider and patient characteristics; (2) the National Death Index (NDI), a centralized database of death record information on file in state vital statistics offices; and (3) a Data Linkage Program, which has substantial statistical and methodological expertise in creating, managing and analyzing multisource linked files. In collaboration with NCHS, NORC has linked the NHCS with the NDI and Centers for Medicare & Medicaid Services (CMS) Medicare and Medicaid data files, HUD administrative housing data, and VA data. Linkage algorithms have been developed and assessed, and analytic guidelines were developed to the final linked data files. NORC has also helped NCHS evaluate privacy protected record linkage (PPRL) software by comparing the accuracy and robustness of commercially available PPRL software to traditional linkage methods utilized by NCHS.
Based on work done for the Department of the Interior Office of Historical Trust Accounting, Ed and NORC colleagues published an Annals of Applied Statistics article describing the methodology used to estimate that amount of unaccounted for money belonging to individuals Indians in the Indian Trust. The estimate has been used by the U.S. District court as part of settlement in a long-standing court case of individual Indian account holders.
Prior to joining NORC, Ed was a Director in the National Economic Consulting Group, Washington National Tax Services office, PricewaterhouseCoopers LLP, and prior to that was a Senior Manage in the Quantitative Economics and Statistics Group at Ernst & Young LLP. His work included the development and use of statistical sampling in support of tax reporting for the filing of current and amended returns, and to develop performance measure comparisons for a regional telephone company. Ed provided expert witness testimony to Public Service Commissions in eight states regarding the need for generic performance measurements, benchmarks, and enforcement mechanisms incumbent telecommunications companies.
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Education
PhD
Colorado State University
MS
University of Utah
BA
Illinois Wesleyan University
Appointments & Affiliations
Board of Directors
Council of Professional Associations on Federal Statistics
Accredited Professional Statistician
American Statistical Association
Honors & Awards
Chair | 2022
ASA Section on Statistical Graphics
Fellow | 2014
American Statistical Association
Project Contributions
Publications
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opens in new tab“Testing Perceptual Accuracy in a U.S. General Population Survey Using Stacked Bar Charts”
Journal Article | March 13, 2024
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opens in new tabDiscussion and Practical Application of Data Visualization Best Practices using Survey Data
Webinar | February 10, 2022
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opens in new tabVisual Communication of Data: It Is Not a Programming Problem, It Is Viewer Perception
Chapter | February 17, 2021
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opens in new tab"Using Statistical Matching to Account for Coverage Bias When Combining Probability and Nonprobability Samples."
Journal Article | August 26, 2020
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Ed Mulrow to Lead NORC at the University of Chicago’s Statistics and Methodology Department
Press Release | October 15, 2019
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"Total Survey Error: Approaches for Measuring Bias and Variance Components When Combining Probability and Non-Probability Samples."
Journal Article | August 26, 2019
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"Exploring Hybrid Methods for Estimation with Combined Probability and Nonprobability Samples."
Journal Article | August 26, 2019
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opens in new tab"Evaluating Estimation Methods for Combining Probability and Nonprobability Samples through a Simulation Study."
Journal Article | August 26, 2019