Announcements

Call for Submissions: Journal for Survey Statistics and Methodology

Special Issue: Survey Research from Asia-Pacific, Africa, the Middle East, Latin America, and the Caribbean

Guest Editors:  Carolina Franco, Mamadou Diallo, Sunghee Lee, Denise Britz do Nascimento Silva

The Journal for Survey Statistics and Methodology seeks submissions for a special issue on survey research from Asia-Pacific, Africa, the Middle East, Latin America, and the Caribbean

Survey research stands to benefit from examining the richness of applications, ideas, and contributions from investigators around the world.  This issue aims to highlight work from locations that are typically underrepresented in JSSAM and other leading journals.  In keeping with the theme of the special issue, it is desirable for at least one of the authors in a submission to be working in one of the regions covered, and applications must use data primarily from these regions. The issue will showcase interesting survey papers from various countries.  

We seek papers from the targeted regions on the usual topics covered in the journal.   These include papers on Survey Statistics, Survey Methodology, and Applications.  The Survey Statistics section presents papers on innovative sampling procedures, imputation, weighting, measures of uncertainty, small area inference, new methods of analysis, and other statistical issues related to surveys. The Survey Methodology section presents papers that focus on methodological research, including methodological experiments, questionnaire design and testing, methods of data collection, interviewer effects, nonresponse and recruitment protocols, responsive designs, new data sources, and use of paradata. The Applications section contains papers involving innovative applications of methods and providing practical contributions and guidance, and/or significant new findings.  In addition to the general topics above, the issue also seeks papers on survey methods and statistics in multinational, multiregional, and multicultural contexts, and on capacity building efforts. 

Submissions to the special issue are welcomed through September 30, 2024. Upon submission manuscripts will be peer-reviewed in accordance with standard journal practice and will be published online soon after acceptance. See this information flyer.

 Electronic copies of the manuscripts should be uploaded at https://mc.manuscriptcentral.com/jssam following the manuscript preparation instructions. To ensure consideration in the special issue, authors must include a cover letter that clearly states that the manuscript has been submitted for consideration for the special issue on “Survey Research from Asia-Pacific, Africa, the Middle East, Latin America, and the Caribbean.”  Queries about this special issue should be directed to Carolina Franco at franco-carolina@norc.org.

Announcements List

  • 2026 Annual Meeting Information

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    Please join us at our annual chapter meeting at ISU on February 27! We have created a poster to share with your students (who we encourage to submit a poster for presentation), but all students, faculty, and working professionals are welcome! If you plan to come, please register in advance as lunch will be provided.

    Detailed Schedule: https://stats-tgeorge.quarto.pub/iowaasa_stat_conf/
    Registration link: https://forms.gle/5njBwBXoAUpz6m898

  • Lunchtime virtual technical talk

    Join the Central Indiana Chapter for a virtual lunchtime presentation by Dr. Yong Zang of the IU Department of Biostatistics. This is a free event, but registration via Zoom is required.
     
         Title:  Bayesian Information Borrowing Prior for Longitudinal Data with Informative Dropout
         Speaker:  Dr. Yong Zang
                          Associate Professor
                          IU Department of Biostatistics
         Date:  Tuesday, February 10, 2026, Noon - 1:00 ET
         Register:  register on Zoom
    Abstract
    Borrowing information from historical controls can improve the efficiency of randomized controlled trials (RCTs), but its application to longitudinal outcomes with informative dropout remains limited. We propose two Bayesian mixture priors for longitudinal data information borrowing: the mixture prior for longitudinal data borrowing (MLB) and its self-adapting extension (SLB). Both approaches use a shared-parameter model to handle the informative dropout and apply a mixture prior framework to incorporate historical control data while accounting for possible prior-data conflict. Simulation studies show that the proposed priors yield desirable operating characteristics enabling efficient and rigorous information borrowing. In particular, the SLB prior demonstrates the best overall performance. 
     
    Speaker
    Dr. Yong Zang is a Showalter Scholar at the IU School of Medicine in the Department of Biostatistics and Health Data Science. Yong earned his PhD in 2011 from University of Hong Kong and has been with the Department of Biostatistics since 2016. His research interests include the theoretical, algorithmic, and software development for adaptive clinical trial design and analysis, methods and testing for statistical genetics, and Bayesian analysis.