Call for Papers
Seeking abstracts for general overview papers that summarize and integrate current knowledge, papers that identify and address future research challenges, innovative theoretical essays, and other papers that describe new empirical research that advances the field beyond what is currently known about survey methods and their application to health-related issues.
The Eleventh Conference on Health Survey Research Methods (HSRMC) will continue the series that began in 1975 to discuss new, innovative survey research methods that improve the quality of health survey data. The HSRMC will bring together researchers from various disciplines who are at the forefront of survey methods research, who are responsible for major health surveys, and who use survey data to develop health policy.
Williamsburg, VA, will host the Health Survey Research Methods conference for the third time in March 2020. Just a short walk from the historic district, the Williamsburg Lodge offers numerous amenities and provides several on-site venues for conference attendees to meet informally or just relax.
Williamsburg VA will be the site for the Health Survey Research Methods Conference in March 2020. It is the third time Williamsburg will host the event in its 45-year history. Just a short walk from the historic district, the Williamsburg Lodge offers many amenities and provides several on-site venues for conference attendees to meet informally or just relax.
Conference attendance will be limited to approximately 90 invited individuals who will present papers, chair sessions, discuss presentations and the state of knowledge in specific areas, and serve as rapporteurs. Food and lodging costs will be covered for attendees, and we are exploring funding to support transportation expenses. Those attendees who have institutional support will be encouraged to cover their own travel, in order to increase resources available to support more junior attendees.
All participants must be present for the entire conference. The steering group is engaged in conversations with several journals about producing one or more special issues from the conference. Learn about proceedings from past conferences.
Williamsburg Lodge, 310 South England Street, Williamsburg, VA, United States (in the heart of the historic area).
Robert Furberg conducts future-oriented research on technology-enabled health behavior change interventions. He receives support from the National Institutes of Health, Centers for Disease Control and Prevention, and the Defense Advanced Research Projects Agency for work that explores how sensor-based biometric data can be used to better support both individualized prevention strategies and public health surveillance. Under Dr. Furberg’s leadership, RTI has contributed several highly cited on wearable device performance, data quality, research methods, and data management. In addition to his scientific responsibilities, Dr. Furberg serves as a committee member on RTI’s Institutional Review Board and several data standards working groups for the Institute of Electrical and Electronics Engineers and Consumer Technology Association.
Kristen Olson’s research examines interviewer effects, paradata, the intersection of nonresponse and measurement errors, within-household selection in self-administered surveys, survey costs, and questionnaire design. Her research has appeared in journals including Public Opinion Quarterly, the Journal of Survey Statistics and Methodology, Sociological Methodology, the Journal of the Royal Statistical Society, Series A, Sociological Methods and Research, Social Science Research, the Journal of Official Statistics, and Field Methods, among others. She is an elected Fellow of the American Statistical Association. Dr. Olson has a B.A. degree in mathematical methods in the social sciences and sociology from Northwestern University, an M.S. degree in survey methodology from the Joint Program in Survey Methodology at the University of Maryland, College Park, and a Ph.D. in survey methodology from the University of Michigan.
Philip Resnik’s research focuses on computational linguistics, with interests both in the application of natural language processing techniques to practical problems such as machine translation and sentiment analysis, and in the modeling of human linguistic processes (especially related to lexical semantics). His general research agenda for language technology is to improve the state of the art by finding the right balance between knowledge-free statistical modeling and linguistically informed techniques -- and in so doing, to obtain a better scientific understanding of human language itself.