Split Questionnaire Designs for Online Surveys: The Impact of Module Construction on Imputation Quality

Abstract: Established face-to-face surveys encounter increasing pressures to move online. Such a mode switch is accompanied with methodological challenges, including the need to shorten the questionnaire that each respondent receives. Split Questionnaire Designs (SQDs) randomly assign respondents to different fractions of the full questionnaire (modules) and, subsequently, impute the data that are missing by design. Thereby, SQDs reduce the questionnaire length for each respondent. Although some researchers have studied the theoretical implications of SQDs, we still know little about their performance with real data, especially regarding potential approaches to constructing questionnaire modules. In a Monte Carlo study with real survey data, we simulate SQDs in three module-building approaches: random, same topic, and diverse topics. We find that SQDs introduce bias and variability in univariate and especially in bivariate distributions, particularly when modules are constructed with items o

Object Details

• Location: Deutsche Nationalbibliothek Frankfurt am Main
• Extent: Online-Ressource
• Language: Englisch
• Notes: Postprint ; begutachtet (peer reviewed) ; In: Journal of Survey Statistics and Methodology (2022) OnlineFirst ; 1-27

Classification and Topics

• Classification: Sozialwissenschaften, Soziologie, Anthropologie

Contributors, Places and Time

• Event: Veröffentlichung
• (where): Mannheim
• (who): SSOAR, GESIS – Leibniz-Institut für Sozialwissenschaften e.V.
• (when): 2022
• Creator: Axenfeld, Julian B. ; Blom, Annelies G. ; Bruch, Christian ; Wolf, Christof

Further information

• DOI: 10.1093/jssam/smab055
• URN: urn:nbn:de:101:1-2023072609391941342330
• Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Last update: 25.03.2025, 1:54 PM CET