GESIS Training Courses
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Scientific Coordination

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

Administrative Coordination

Angelika Ruf
Tel: +49 221 47694-162

Short Course D: Mixed-Mode Surveys

About
Location:
Online via Zoom
 
General Topics:
Course Level:
Format:
Software used:
R or Mplus
Duration:
3 days
Language:
Fees:
Students: 200 €
Academics: 300 €
Commercial: 600 €
 
Keywords:
Additional links
Lecturer(s): Dr. Sven Stadtmüller, Dr. Henning Silber, Prof. em. Dr. Peter Schmidt

About the lecturer - Dr. Sven Stadtmüller

About the lecturer - Dr. Henning Silber

About the lecturer - Prof. em. Dr. Peter Schmidt

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 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 on statistical methods for testing measurement equivalence of multi-item scales for mixed-mode and mixed-device survey data employing confirmatory factor analysis with multiple groups representing different modes. Furthermore, we demonstrate its use with prepared examples using the programs R-lavaan, Mplus Automation, and Mplus.
 
The detailed syllabus with course times and literature will be available soon.


Target group

Participants will find the course useful if:
  • they plan or conduct their own mixed-mode survey;
  • they plan to use or already use data from mixed-mode surveys;
  • they aim for a better understanding of the peculiarities of mixed-mode surveys.


  • Learning objectives

    By the end of the course participants will:
  • have a general understanding of advantages and disadvantages of survey modes and of mixing them with 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 online short course with a total amount of 12 hours of class time. The course structure includes a mix of teaching and exercises, and Q&A sessions. Exercises will be divided in group and individual exercises.
  • During the exercises, lecturers will be available to support the learning process.
  • Each learning block, we will conclude with a Q&A session.


  • Prerequisites

  • Basic knowledge in quantitative social sciences; practical experience in conducting surveys will be beneficial
  • Basic knowledge of multivariate statistics, esp. factor analysis
  • Experiences with R/R Studio and/or MPlus
  •  
    Software and Hardware Requirements
    You should have access to R or Mplus to perform individual exercises. Specifically, for the structural equation models used to test for measurement equivalence, you will need R-lavaan or Mplus version 8.7 and Mplus Automation. Please note that the free version of Mplus meets the requirements of our course in terms of number of observed variables used.