André is interested in using advanced statistical models to provide insight and understanding for issues across health and social care, with an emphasis on statistical robustness and rigorous estimation of uncertainty.
He has experience applying experimental methods, and a wide variety of quasi-experimental methods, such as difference-in-differences, instrumental variables, and synthetic control, across a wide variety of contexts including health, social care, youth violence, education and psychological research.
André is particularly interested in approaches which adjust for measurement error within the context of latent variables, such as Item Response Theory and Structural Equation Modelling (particularly using Model Implied Instrumental Variables).
- Complex modelling
- Evaluation and impact assessment
André previously worked for a Third Sector organisation who conducted evaluations across the health and social care spaces. This included leading the quantitative component of impact evaluations, from evaluations of very small interventions, such as a mentorship programme with only two employees aimed at reducing youth violence, to evaluations of very large programmes, such as a multi-million pound city-wide programme of voluntary sector activities aimed at reducing demand for adult social care.
André has a master’s degree in research methodology, during which he used Bayesian ordinal hierarchical regression to better understand the processes underpinning subjective attributions of happiness.