<abstract xmlns="http://www.w3.org/1999/xhtml"><p>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 nonresponse, potentially leading to biased results. One of the main reasons for dropout is the burden of repeatedly responding to long questionnaires. Advancements in survey administration methodology and multiple imputation software now 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 limited. Using simulations and data from the Health and Retirement Study (HRS), we compare the performance of several methods for administering a split questionnaire design in the longitudinal setting. The results suggest that the optimal design depends on the data structure and estimand of interest. These factors must be taken into account when designing a longitudinal study with planned missing data.</p></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 nonresponse, potentially leading to biased results. One of the main reasons for dropout is the burden of repeatedly responding to long questionnaires. Advancements in survey administration methodology and multiple imputation software now 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 limited. Using simulations and data from the Health and Retirement Study (HRS), we compare the performance of several methods for administering a split questionnaire design in the longitudinal setting. The results suggest that the optimal design depends on the data structure and estimand of interest. These factors must be taken into account when designing a longitudinal study with planned missing data.

Three-Form Split Questionnaire Design for Panel Surveys

Department of Biostatistics, School of Public Health

Journal of Official Statistics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Three-Form Split Questionnaire Design for Panel Surveys"}

Longitudinal or panel surveys are effective tools for measuring individual level changes in the outcome variables and their correlates. One drawback of these...

Three-Form Split Questionnaire Design for Panel Surveys

Publié en ligne: 10 déc. 2020

Pages: 827 - 854

Reçu: 01 oct. 2018

Accepté: 01 avr. 2020

DOI: https://doi.org/10.2478/jos-2020-0040

© 2020 Paul M. Imbriano et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.