Research Program on Clinical Prediction ModelsPurposeWe aim to develop simulators of pathological states in human populations with chronic diseases, that can estimate the rates of specific clinical events and states in the future.MethodsOn the base of stochastic models of the population (StoMP) we compute joint probability distributions of measurables that can be fit against observed distributions.In principle, all credible observations should be explained by the StoMP, not unlike a meta-analysis in which a common model fits all available studies. In StoMPs, unlike in a classical meta-analysis, the model is, however, fit by different types of studies, using different observation clusters each, while in the meta-analysis, the model and each of the fit studies are the same. The StoMP is also very different from that underlying each observation study, and may include parameters and stochastic functions that are not directly measurable. A simple StoMP example is a farmacometric model. Developing StoMPs involves the following broad steps:
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