IASS Webinar 16: Three-Form Split Questionnaire Design for Panel Surveys

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Date/Time
Date(s) - 27/04/2022
2:00 pm - 3:30 pm

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IASS Webinar 16: Three-Form Split Questionnaire Design for Panel Surveys

27 April 2022 at 2pm – 3:30pm (CET)

 

All are invited to the webinar, organised by the International Association for Survey Statisticians.

 

Please register for the IASS Webinar at:

 

https://register.gotowebinar.com/register/6985474868736161038

 

After registering, you will receive a confirmation email containing information about joining the webinar. There will be time for questions. The webinar will be recorded and made available on the IASS and ISI web site. See below for the abstract and biography of the speakers.

 

Webinar Abstract

 

Longitudinal or panel surveys are effective tools for measuring individual level changes in the outcome variables and their correlates.  One drawback of these studies is dropout or non-response, potentially leading to biased results. One potential reason for dropout is the burden placed on subjects for repeatedly responding to long questionnaires. Advancements in survey administration methodology and multiple imputation software make it possible for planned missing data designs to be implemented for improving the data quality through a reduction in survey length. Many papers have discussed implementing a planned missing data study using a split questionnaire design in the cross-sectional setting, but development of these designs in a longitudinal study has been fairly limited. We propose several methods for implementing split questionnaire designs in the longitudinal setting. Using both simulations and data from a longitudinal study, we compare the performance of these methods. The results suggest that the optimal design depends on both the data structure and estimate of interest. These factors should be taken into account when designing a longitudinal study with planned missing data.

Biography

Paul Imbriano graduated from University of Michigan with a PhD in Biostatistics in 2018. His thesis work focused on missing data and planned missing data designs for surveys. He was also involved in research projects involving multiple imputation and combining information from multiple data sources. Since his graduated, his have worked at the US FDA as a statistical reviewer for clinical trials. He currently works on trials in the therapeutic areas of gastroenterology, hepatology, and COVID-19.