Vera Vogel, Chair for Cross-Cultural Social and Personality Psychology: Statistical Modelling Techniques (October 2022)

Vera Vogel has been a doctoral candidate at the Chair for Cross-Cultural Social and Personality Psychology of Prof. Dr. Jochen Gebauer since 2020. Her research focuses on social perception, categorisation & stereotypes, self-concept and social class affiliation. Previously, she studied psychology at the University of Mannheim and Swansea University in Wales, UK.

What is your current research topic?

What particular sparked my interest is the question how different social environments influence how people feel, think, and behave. In my current research project, I investigate well-being benefits when people match with specific social groups. For example, wealthy people are especially happy when they live in wealthy societies. But which social group (e.g., people with the same gender, same age, or same world view) exerts the biggest effect on people´s well-being? And do people have to perceive the match in order to experience the well-being benefits? Exceeding classical investigations, I created a methodological toolkit in the context of large-scale analyses to address these novel substantial questions.

For those who have not yet delved deeply into the topic of Data Science: How would you explain to a child what you are working on?

Researchers asked people all over the world about their attitudes, values, and well-being. The answers are gathered and saved on specific platforms. Fortunately, most researchers share their data so that other researchers can use the data to answer their own research questions. For example, I can investigate whether conservative people are especially happy when they live in conservative societies.

Everyone talks about Data Science – how would you describe the importance of the topic for yourself in three words?

Grab real-world patterns

What points of contact with Data Science does your work have? Which methods do you already use, and which would be interesting for you in the future?

For my research, I use large-scale datasets including people from all over the world (< 10 million respondents across 65 countries). Thus, I am able to draw conclusions not only on a national level but also to investigate sociodemographic cross-cultural variations. To account for the nesting of people in different countries or social groups, I conduct different multilevel models (e.g., linear mixed-effects models or cross-classified models) with the statistic software Julia. In the future, I want to focus on people´s social networks and investigate their network structure.

How high is the value of Data Science for your work? Would your research even be possible without Data Science?

In order to grab nuanced and robust result patterns and to also draw generalizable conclusions, I use datasets with more than 10 million respondents. Without adequate large-scale data, adequate statistical modelling techniques, and adequate computer power, it would not be possible to capture person-culture match effects in the real world.

What development opportunities do you see for the topic of Data Science in relation to your field?

Future research has to use the amount of data people generating in their everyday lives (sometimes more, sometime less conscious). In my mind, however, this does not replace the need to a-priori think critically of one´s research questions and the underlying mechanisms. Only by combining efficient large-scale analyses with a profound rational thinking about the underlying mechanisms, we as researchers are able to conduct ambitious, innovative and, impactful research projects.