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A note on obtaining correct marginal predictions from a random intercepts model for binary outcomes.
BACKGROUND: Clustered data with binary outcomes are often analysed using random intercepts models or generalised estimating equations (GEE) resulting in cluster-specific or 'population-average' inference, respectively. METHODS...
Estimation of required sample size for external validation of risk models for binary outcomes
Risk-prediction models for health outcomes are used in practice as part of clinical decision-making, and it is essential that their performance be externally validated. An important aspect in the design of a validation study is...
How to develop a more accurate risk prediction model when there are few events.
When the number of events is low relative to the number of predictors, standard regression could produce overfitted risk models that make inaccurate predictions. Use of penalised regression may improve the accuracy of risk...
Estimation of required sample size for external validation of risk models for binary outcomes.
Risk-prediction models for health outcomes are used in practice as part of clinical decision-making, and it is essential that their performance be externally validated. An important aspect in the design of a validation study is...