GESIS Training Courses

Scientific Coordination

Sebastian E. Wenz
Tel: +49 221 47694-159

Administrative Coordination

Jacqueline Schüller
Tel: +49 0221 47694-160

Short Course E: Mixed-Mode Surveys

Online via Zoom
Course Duration
Wed - Fr: 10:00-15:00 CEST
General Topics:
Course Level:
Software used:
R or Mplus
Students: 220 €
Academics: 330 €
Commercial: 660 €
Additional links
Lecturer(s): Sven Stadtmüller, Peter Schmidt, Yannick Diehl, Henning Silber

About the lecturer - Sven Stadtmüller

About the lecturer - Peter Schmidt

About the lecturer - Yannick Diehl

About the lecturer - Henning Silber

Course description

Due to decreasing response rates around the world, survey designers must explore new ways of recruiting respondents for their surveys. One popular option is to offer different modes for survey participation, thus allowing target persons to participate in the survey mode that suits them best. While mixing survey modes for data collection can have positive effects on response rates, sample balance, and survey costs, the question arises of whether the data from different survey modes can be easily pooled and compared. This question also applies to data from long-standing survey programs that, in the course of the COVID 19-pandemic, had to refrain from face-to-face surveys and to collect data in other (mostly self-administered) survey modes.
In this short course, we provide an overview of empirical evidence related to the benefits and drawbacks of using multiple modes for data collection and outline some recommendations for the implementation of mixed-mode surveys. Specifically, we will cover topics such as mixed-mode-specific questionnaire design considerations, experimental evidence on comparing mixed-mode surveys with single-mode surveys, and optimal strategies of how to implement them.
The practical part of the course provides an introduction of statistical methods for testing mode effects and measurement equivalence of multi-item scales for mixed-mode and mixed-device survey data. We employ confirmatory factor analysis with multiple groups representing different modes and use regression and structural equation models to test mode effects. Furthermore, we demonstrate its use with prepared examples using the programs R-lavaan, Mplus Automation, and Mplus.
For additional details on the course and a day-to-day schedule, please download the full-length syllabus.

Target group

You will find the course useful if:
  • you plan or conduct your own mixed-mode survey,
  • you plan or use data from mixed-mode surveys,
  • you eventually plan to test mode effects with you own datasets,
  • you aim for a better understanding of the peculiarities of mixed-mode surveys.

Learning objectives

By the end of the course you will:
  • have a general understanding of advantages and disadvantages of survey modes and of mixing them within a data collection,  
  • have a general understanding of the peculiarities of mixed-mode surveys regarding nonresponse and measurement error as well as questionnaire design,
  • have a general understanding of procedures for testing measurement equivalence of survey data collected via different survey modes/devices and its implementation in R-lavaan and Mplus.
Organizational structure of the course  
This is a three-day short course with a total amount of 12 hours of virtual class time. The course structure includes a mix of teaching and exercises. Exercises will be divided in group and individual exercises. During the exercises, lecturers will be available to support the learning process.


  • Basic knowledge in quantitative social sciences; practical experience in conducting surveys will be beneficial
  • Basic knowledge of multivariate statistics, esp. confirmatory factor analysis
  • Experience with R/R Studio and/or MPlus
Software and hardware requirements
You require a computer or laptop to successfully participate in this course.
You should have access to R or Mplus to perform individual exercises. Specifically, for confirmatory factor analysis to test for measurement equivalence and for regression models and SEM models, you will need R-lavaan or Mplus version 8.7 and upwards. Please note that the free version of Mplus meets the requirements of our course in terms of the number of observed variables used.

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