I’m a social psychologist interested in intergroup contact and conflict, social identity, social inequality, and social change. I investigate these topics using advanced quantitative methods.
I studied psychology and social sciences at University College Maastricht (BA) and at the University of Oxford (MSc in Psychological Research, DPhil in Experimental Psychology).
I have recently submitted my doctoral thesis, and am now a postdoctoral researcher at the Oxford Centre for the Study of Intergroup Conflict.
Intergroup contact and social identity
I study whether intergroup contact changes not only how we see others, but also how we see ourselves. In my thesis, I examined whether contact with sexual and gender minorities fosters more continuous and fluid conceptions of sexuality and gender, and whether contact with caste and religious outgroups fosters more inclusive national identities.
Intergroup contact and social change
I study how positive and negative contact shape support for social change in advantaged and disadvantaged groups. I found that positive contact encourages solidarity-based collective action among the advantaged, while negative contact encourages collective action among the disadvantaged (Reimer et al., 2017). I am currently preparing a meta-analysis on this topic.
I study whether large-scale contact-based interventions can foster social integration and cross-group solidarity. I have worked with The Challenge Network to evaluate a nation-wide intervention focused on fostering social integration among adolescents of different ethnic and socio-economic backgrounds. I am currently working on an evaluation of the Shared Education programme in Northern Ireland.
Responding to social injustice
I study how people respond to social injustice that benefits their own group. I am currently examining defensive responding to implicit bias feedback, as well as how advantaged-group members evaluate collective actions by disadvantaged outgroups.
Network of my collaborators around the world.
Bayesian Data Analysis
I use Bayesian data analysis (implemented in Stan) as a flexible and powerful approach to statistical inference. I have experience with multilevel, multivariate, logistic and ordinal regression, item response, and missing data models—as well as various combinations of these approaches. I use cross-validation and stacking to compare and combine model predictions.
Prior, likelihood, and posterior distributions for parameter p (the probability of heads) after observing k = 6 heads in n = 10 coin flips.
I use multilevel models to solve a broad range of data analysis challenges—including nested data, longitudinal data, and multiple comparison problems. I teach multilevel modeling to graduate students at University of Oxford.
Each person’s probability of observing heads, estimated with complete pooling (left), partial pooling (middle), and no pooling (right) across ten persons. Multilevel models result in partial pooling, and thus overcome multiple comparison problems.
Structural Equation Models
I use structural equation models (lavaan, Mplus) for scale development and to analyse longitudinal surveys. I have experience with cross-lagged panel models, latent growth models, and with more recent approaches to modeling longitudinal data.
I use ggplot2 as a flexible approach to data visualisation. I have experience with a broad range of visualisations, including maps, networks, and flow diagrams. I teach data visualisation to graduate students at University of Oxford.
Example of a data visualisation for a recent paper (in preparation).