Are you interested in teaching a Continuing Education Course (CEC) on a topic related to survey research methods at 2025 JSM? If yes, please email me the title, a short abstract (1 paragraph) and a short bio of each instructor at Julia.Soulakova@ucf.edu. A few examples of potential topics are listed below. Here is some additional information from the ASA Professional Development Program CEC Proposal Guide:
The content of the course might fulfill any one of the following class descriptions:
• An in-depth presentation of a specific area of statistical theory, methodology, or application. The material covered may focus on "cutting edge" methods or other more established topics;
• A broad overview of an established area of statistical theory or methodology suitable either as a refresher "course" or as an introduction to the field for those not exposed to it in previous training;
• A description of a statistical method and its application using one or more software tools- as long as there is significant content material described in the proposal.
Note: Presentations offered by vendors of a software product should consider proposing a Computer Technology Workshop (CTW) rather than a course. No CE offering should be a software "infomercial." Those offerings that are heavily software dependent should be proposed as a CTW.
· Honoraria Allotments for CEC Program
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Course Length
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Number of Instructors
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Honorarium
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2-day
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1
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$4,750
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2 or more
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$5,500
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1-day
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1
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$2,750
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2 or more
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$3,500
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1/2-day
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1 or more
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$2,000
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EXAMPLES OF POTENTIAL TOPICS
· Adaptive and responsive survey designs and strategies for improving response rate
· Application of AI to post data processing: coding, editing, imputation, and weighting
· Capture-recapture surveys, respondent-driven sampling, and alternative methods for including hard-to-reach populations
· Current practices and challenges in panel surveys, including the use of dependent interviewing and panel conditioning
· Current topics on public use files: statistical disclosure control, synthetic data, formal privacy
· Gridded population survey sampling techniques
· Identifying data quality issues and potential falsification in self-administered and interviewer-administered surveys
· Innovative software tools for analysis of survey data, e.g., nonprobsvy package in R for analysis of non-probability surveys
· Latent trend models and other innovative approaches for analyzing survey data
· Learning from data collected using non-probability sampling, e.g., machine learning techniques for analysis of electronic health records
· Methods for handling missing values in surveys
· Survey sampling tailored to underserved communities
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Julia Soulakova
2023-24 SRMS Education Officer
Professor of Medicine
University of Central Florida
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