Quantitative social science has long been dominated by self-consciously positivist approaches to the philosophy, rhetoric and methodology of research. This article outlines an alternative approach based on interpretive research methods. Interpretative approaches are usually associated with qualitative social science but are equally applicable to the analysis of quantitative data. In interpretive quantitative research, statistics are used to shed light on the unobservable data generating processes that underlie observed data. Key tenets of interpretive quantitative methodology are the triangulation of research results arrived at by analysing data from multiple perspectives, the integration of measurement and modelling into a more holistic process of discovery and the need to think reflexively about the manner in which data have come into existence. Interpretive quantitative research has the potential to yield results that are more meaningful, more understandable and more applicable (from a policy standpoint) than those achieved through conventional positivist approaches.