Large routinely collected, clustered databases, such as QResearch, and multicentre studies are a huge resource for medical research offering more insight into patient and clinical pathways. These datasets are being used extensively for developing and validating clinical prediction models which are used widely to inform medical decision making. However, clustering in these datasets is often ignored in prediction modelling studies, and valuable information is lost as a result. In this talk we will cover how to get the most out of using large routinely collected and clustered datasets for predicting modelling research.
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