Riet earned her PhD in Psychological Methods from the University of Amsterdam. Her PhD project focused on developing methods to distinguish network models and latent variable models both empirically and theoretically. Her interest in comparing these different modeling frameworks ties in with her broader interest in philosophy of statistics and the interpretation of statistical models. Some examples: What are the implications of interpreting the common factor in a common factor model as a summary of the data rather than as an underlying common cause? What are possible chance experiments that result in the response variables in a factor model or IRT model being ‘random variables’? What is actually ‘observed’ in ‘observed variables’?