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Clinical Prediction Models
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TLDR
This paper presents a case study on survival analysis: Prediction of secondary cardiovascular events and lessons from case studies on overfitting and optimism in prediction models.Abstract:
Introduction.- Applications of prediction models.- Study design for prediction models.- Statistical models for prediction.- Overfitting and optimism in prediction models.- Choosing between alternative statistical models.- Dealing with missing values.- Case study on dealing with missing values.- Coding of categorical and continuous predictors.- Restrictions on candidate predictors.- Selection of main effects.- Assumptions in regression models: Additivity and linearity.- Modern estimation methods.- Estimation with external methods.- Evaluation of performance.- Clinical usefulness.- Validation of prediction models.- Presentation formats.- Patterns of external validity.- Updating for a new setting.- Updating for a multiple settings.- Prediction of a binary outcome: 30-day mortality after acute myocardial infarction.- Case study on survival analysis: Prediction of secondary cardiovascular events.- Lessons from case studies.read more
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The South African Surgical Outcomes Study: A 7-day prospective observational cohort study.
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A Panel of Novel Biomarkers Representing Different Disease Pathways Improves Prediction of Renal Function Decline in Type 2 Diabetes
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