Survival data can contain an unknown fraction of subjects who are 'cured' in the sense of not being at risk of failure.We describe such data with cure-mixture models, which separately model cure status and the hazard of failure among non-cured subjects.No diagnostic currently exists for evaluating the fit of such models; the popular Schoenfeld residual (Schoenfeld, 1982.Partial residuals for the proportional hazards regression-model. Biometrika69, 239.241) is not applicable to data with cures.In this article, we propose a pseudo-residual, modeled on Schoenfeld's, to assess the fit of the survival regression in the non-cured fraction.Unlike Schoenfeld's approach, which tests the validity of the proportional hazards (PH) assumption, our method uses the full hazard and is thus also applicable to non-PH models.We derive the asymptotic distribution of the residuals and evaluate their performance by simulation in a range of parametric models.We apply our approach to data from a smoking cessation drug trial.