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virtual

Survey Design

Course Dates and Times

Date: Monday 5 – Friday 9 February 2024
Duration: 3 hours of live teaching per day
Time: 13:30 – 16:45 CET

Julia Partheymüller

julia.partheymueller@univie.ac.at

University of Vienna

This course will provide you with a highly interactive online teaching and learning environment, using state of the art online pedagogical tools. It is designed for a demanding audience (researchers, professional analysts, advanced students) and capped at a maximum of 16 participants so that the teaching team can cater to the specific needs of everyone.

Purpose of the course

Survey research has seen remarkable growth in recent decades, driven in large part by the emergence of online surveys, which have significantly reduced the costs associated with conducting surveys.

This advancement has opened up new research opportunities, enabling a growing number of researchers to independently run surveys. However, to ensure the validity of inferences drawn based on these surveys, careful attention must be paid to various methodological aspects of survey design. In particular, sampling and measurement methods but also research design and questionnaire design can exert a profound influence on data quality and inference validity.

Against this background, this course has been designed to equip participants with the essential knowledge and skills to effectively plan, design, and conduct their own surveys.

ECTS Credits

4 credits - Engage fully in class activities and complete a post-class assignment


Instructor Bio

Julia Partheymüller is a Senior Scientist at the Department of Government at the University of Vienna. 

Julia possesses extensive experience in survey design, being an integral member of the team of the Austrian National Election Study (AUTNES). She has contributed to various other projects involving large-scale survey data collection, including the Austrian Corona Panel Project (ACPP), Reconciling Europe with its Citizens through Democracy and Rule of Law (RECONNECT), and the German Longitudinal Election Study (GLES).

Her research focuses on the nature and origins of public perceptions, attitudes, and behaviours, with a strong emphasis on quantitative methods. She is particularly interested in refining measurement techniques and leveraging the potential of longitudinal and experimental survey designs to enhance causal inference.

@schnizzl

Key topics covered

This course covers the key stages of the survey research lifecycle. You will start out by tackling fundamental questions of research design that typically precede data collection. Following that, you will be provided with the opportunity to discuss the implications of various sampling methods, including those of probability and non-probability sampling strategies. Subsequently, the focus will shift to addressing various measurement techniques and you will learn how to translate theoretical constructs into survey questions. Moving on, the course delves into the realm of survey experiments that have been a major driver of innovation in many applied fields.

Finally, you will learn how to assess data quality after data collection has been completed and explore best practices for disseminating research findings and sharing survey data.

Day 1: Fundamentals of Research Design

Before designing a survey, fundamental decisions regarding the research design need to made. You will learn about  cross-sectional and longitudinal survey designs and their implications for the kind of inferences that can be drawn. In addition to this, legal and ethical standards to consider before conducting a survey will be explored.

Day 2: Sampling Methods

You will learn about various kinds of probability and non-probability sampling designs and survey modes (e.g., personal, telephone, and online surveys). Discussion will take place and be centred on their strengths and weakness and cover approaches to encourage survey participation such as incentives.

Day 3: Measurement Techniques and Questionnaire Design

You will be introduced to various measurement techniques and learn about the effects of questionnaire design on measured outcomes. Criteria and tools to evaluate the quality of survey questions and examine best practice (and worst practice) examples will be addressed.

Day 4: Survey Experiments

The course will delve into the captivating realm of survey experiments, allowing for the exploration of causal relationships and the investigation of the impact of specific interventions. You will learn how to design different kinds of survey experiments that can be embedded in your surveys, including simple randomizations and more complex factorial designs.

Day 5: Data Quality Assessment and Best Practices for Dissemination

On the final day of the course, you will learn about the criteria of data quality assessments and how to correct potential biases after data collection, for example, by post-stratification weights. Discussion will focus on guidelines for reporting survey-based research findings and best practices of data-sharing and data protection.


How the course will work

Prior to the live sessions, you will have access to introductory pre-recorded lectures, recommended readings, and self-assessment quizzes. These resources are designed to provide you with a solid foundation and enable you to prepare effectively for the course.

Throughout the live sessions, a mix of various instructional methods will be utilised. The instructor will deliver short input lectures to provide essential insights and knowledge. Interactive in-class discussions and collaborative group exercises will further reinforce your understanding of survey design and enhance their methodological skills.

Moreover, you will be encouraged to actively engage in the learning process by bringing your own survey projects and related questions to the table. The course offers a valuable opportunity for feedback and guidance on participants' individual research endeavors, fostering a hands-on and practical approach to learning.

While some familiarity with survey research and quantitative methods may be beneficial, they are not required for participation and the successful completion of the course.