A systematic approach to understanding trade-offs when designing & remodeling social surveys

In this online course, we outline a comprehensive framework for understanding the trade-offs involved in designing and remodelling social surveys. Our framework is rooted in the Total Survey Error and Total Survey Quality approaches, balancing the need to reduce sources of error against the constraints of a project, time and costs. Through real-life examples and case studies, we discuss the advantages and disadvantages of different research designs, with a focus on mixed-mode surveys, and the key steps involved in making informed decisions and remodelling surveys.

This course is for anyone involved in the design of survey research and will be particularly relevant for those who are running an existing survey and exploring alternative modes of data collection.

Course Description

The course covers:

• Theoretical frameworks and their applications in optimal survey design
• The risks of measurement and selection effects
• Advantages and disadvantages of various research designs, with a focus on mixed-mode surveys
• Trade-offs in designing and remodelling social surveys
• Key steps in making informed decisions when designing and remodelling surveys

By the end of the course participants will:

• Be familiar with the application of the Total Survey Error and Total Quality frameworks for optimal survey design
• Improve their research design skills and their ability to evaluate and critique existing designs
• Have a better knowledge of the advantages and disadvantages of different research designs, with a focus on mixed-mode surveys
• Understand the trade-offs involved in designing and remodelling social surveys
• Understand the key steps involved in designing and remodelling social surveys

Pre-requisites:

Participants need familiarity with the design of survey research, either through coursework or work experience. A basic understanding of quantitative research methods, and survey concepts is expected. No experience with data analysis software is required for this course.