It is better to use all available data for model development (ie, avoid data splitting), with resampling methods (such as bootstrapping) used for internal validation Larger sample sizes lead to the development of more robust modelsĭata should be of sufficient quality and representative of the target population and settings of application Patients and healthcare professionals require clinical prediction models to accurately guide healthcare decisions Correspondence to: R D Riley r.rileykeele.ac.uk (or on Twitter).6Department of Clinical Epidemiology, Leiden University Medical Center Leiden, Netherlands.5Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.4Julius Center for Health Sciences, University Medical Center Utrecht, Utrecht, Netherlands.3Division of Informatics, Imaging and Data Science, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.2Department of Biostatistics, Vanderbilt University School of Medicine, Nashville TN, USA.1Centre for Prognosis Research, School of Primary, Community and Social Care, Keele University, Staffordshire ST5 5BG, UK.Maarten van Smeden, assistant professor 4 5 6.Gary Collins, professor of medical statistics 5,.
Karel G M Moons, professor of clinical epidemiology 4,.Johannes B Reitsma, associate professor 4,.
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