Handling bias in analysis of mixed-mode survey data
Date:
30/04/2026
Organised by:
UCL Centre for Longitudinal Studies (CLS)
Presenter:
Dr. Liam Wright, Prof. Richard Silverwood, Dr. Georgia Tomova
Level:
Entry (no or almost no prior knowledge)
Contact:
Richard Steele, Events and Marketing Officer
Phone: 020 7911 5320
Email: ioe.clsevents@ucl.ac.uk
Venue: Online
Description:
Working with mixed-mode survey data? Join this free webinar, run by CLS and Survey Futures, to understand the challenges of using mixed-mode survey data and learn statistical methods to handle these in practice.
About the event
Surveys are increasingly moving to mixed-mode data collection – such as carrying out interviews via face-to-face, telephone, video and/or web modes.
In this webinar, we will give an overview of issues that arise when using data collected in mixed-mode surveys. This includes the bias introduced when participants respond differently to survey items depending on the survey mode used – termed “mode effects”.
We will conceptualise the bias from mode effects within a simple and intuitive empirical framework called Causal Directed Acyclic Graph (DAG). We will then describe statistical methods for handling mode effects, looking in particular at Quantitative Bias Analysis (QBA).
Why attend?
- Learn about mixed-mode designs and the reasons they can introduce bias in data analyses.
- Find out how you can apply DAGs to easily conceptualise the bias from mode effects.
- Learn statistical methods for handling mode effects, their assumptions and the situations where they may increase bias.
- Learn about QBA.
Who should attend?
Users or managers of mixed-mode survey data, including users of CLS cohort data.
Cost:
Free
Website and registration:
Region:
Greater London
Keywords:
Longitudinal Research , Survey and Questionnaire Design, Longitudinal Data Analysis, Mixed Methods Data Handling and Data Analysis, Mixed Methods Approaches (other), Mode effects, Causal Directed Acyclic Graph (DAG), Quantitative Bias Analysis (QBA)
Related publications and presentations from our eprints archive:
Longitudinal Research
Survey and Questionnaire Design
Longitudinal Data Analysis
Mixed Methods Data Handling and Data Analysis
Mixed Methods Approaches (other)