Abstract Number:
1668
Submission Type:
Topic-Contributed Paper Session
Participants:
Akhil Vaish (1), Phillip Kott (1), Phillip Kott (1), Neeraja Sathe (1), Gauri Datta (2), Akhil Vaish (1), Roderick Little (3), Yulei He (4)
Institutions:
(1) RTI International, N/A, (2) University of Georgia, N/A, (3) University of Michigan, N/A, (4) National Center for Health Statistics, N/A
Chair:
Co-Organizer:
Discussant:
Session Organizer:
Speaker(s):
Yulei He
National Center for Health Statistics
Session Description:
Ralph Folsom Jr., former chief scientist at RTI International and ASA Fellow, passed away on December 14, 2022, in Raleigh, North Carolina. He joined RTI in 1969 as a statistician and became a chief scientist in 1998. While working at RTI, he earned his Ph.D. in biostatistics from UNC in 1984. He was a past member of the National Academy of Sciences' Panel to Evaluate the Survey of Income and Program Participation, the ASA working group to advise Census Bureau staff on the Survey of Income and Program Participation, the Board of Governors for the Panel Survey of Income Dynamics, and the Committee on National Statistics' Panel on Statistical Methods for Measuring the Group Quarter Population in the American Community Survey.
Ralph's 47-year career at RTI was filled with many innovative advancements in the field of survey data analyses. Ralph's early work on developing Taylor series standard errors for balanced effects also extended to Taylor series estimation of sampling errors for regression coefficients, which became the basis for the analysis of complex survey and other clustered data in SUDAAN® (statistical software to analyze clustered correlated data). Ralph was the first to propose using calibration weighting to adjust for unit nonresponse. He made his proposal at the 1991 ASA annual conference (ASA Proc. Soc. Statist. Sec., 197–202) before the concept of calibration weighting was formalized by Deville and Särndal (JASA, 1992). In a series of papers presented at the 2000 ASA annual conference, Ralph went on the generalize the class of calibration weighting schemes proposed by Deville and Särndal to cover their use for nonresponse and coverage-error adjustment in a more scientifically defensible manner.
In the mid-1990s, Ralph started working on developing small area estimation (SAE) methodologies to enable Substance Abuse and Mental Health Services Administration to produce reliable and cost-effective state and local area level estimates in a timely manner. He developed Survey Weighted Empirical Bayes (SWEB) (Folsom and Judkins, June 1997) SAE methodology for unit-level binary outcomes from complex survey data. Subsequently, Ralph developed the full hierarchical Bayes version of SWEB methodology and called it as the Survey Weighted Hierarchical Bayes (SWHB) methodology (Folsom, Shah, Vaish, 1999). Ralph's innovative work on SAE played a critical role in the expansion of the National Survey on Drug Use and Health (NSDUH) in 1999 from a national design to the currently implemented state stratified design. He collaborated with Babu Shah (developer of SUDAAN®) and developed a highly efficient state-of-the-art SWHB software. Since then, SWHB software is being used to produce annual state estimates and biennial substate estimates for 35+ binary NSDUH outcome variables. The NSDUH state estimates on dependence and abuse provide the basis for calculations of treatment need by sub-state region, age, gender, and race presented in the Substance Abuse Prevention and Treatment Block Grant Application.
Proposed papers are directly or indirectly associated with Ralph's work:
"On the Definition of Response Propensities for Survey Nonresponse Adjustments," Prof. Roderick Little
"Ranking of Small Areas: A Bayesian solution," Prof. Gauri Datta
"Bias evaluation for Nonprobability Surveys, A Sensitivity Analysis Approach," Dr. Yulei He
"Unit-level Survey Weighted Hierarchical Bayes Small Area Estimation for Binary Outcomes," Dr. Akhil Vaish
Sponsors:
Government Statistics Section 2
Social Statistics Section 3
Survey Research Methods Section 1
Theme:
Statistics and Data Science: Informing Policy and Countering Misinformation
No
Applied
Yes
Estimated Audience Size
Small (<80)
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I understand and have communicated to my proposed speakers that JSM participants must register and pay the appropriate registration fee by June 1, 2024. The registration fee is nonrefundable.
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