Pages that link to "Item:Q6625939"
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The following pages link to Minimum sample size for developing a multivariable prediction model. II: Binary and time-to-event outcomes (Q6625939):
Displaying 18 items.
- Using temporal recalibration to improve the calibration of risk prediction models in competing risk settings when there are trends in survival over time (Q6560494) (← links)
- Sample size and predictive performance of machine learning methods with survival data: a simulation study (Q6560569) (← links)
- Stability of clinical prediction models developed using statistical or machine learning methods (Q6595097) (← links)
- Sample size determination for prediction models via learning-type curves (Q6615972) (← links)
- Pitfalls and potentials in simulation studies: questionable research practices in comparative simulation studies allow for spurious claims of superiority of any method (Q6625336) (← links)
- Comparison of likelihood penalization and variance decomposition approaches for clinical prediction models: a simulation study (Q6625357) (← links)
- Penalized regression methods with modified cross-validation and bootstrap tuning produce better prediction models (Q6625494) (← links)
- Minimum sample size for developing a multivariable prediction model. I: Continuous outcomes (Q6625938) (← links)
- Developing prediction models to estimate the risk of two survival outcomes both occurring: a comparison of techniques (Q6626839) (← links)
- Propensity-based standardization to enhance the validation and interpretation of prediction model discrimination for a target population (Q6626877) (← links)
- Minimum sample size for external validation of a clinical prediction model with a continuous outcome (Q6627872) (← links)
- Clinical prediction models to predict the risk of multiple binary outcomes: a comparison of approaches (Q6627905) (← links)
- A note on estimating the Cox-Snell \(R^2\) from a reported \(C\) statistic (AUROC) to inform sample size calculations for developing a prediction model with a binary outcome (Q6627931) (← links)
- Individual participant data meta-analysis for external validation, recalibration, and updating of a flexible parametric prognostic model (Q6628089) (← links)
- Developing more generalizable prediction models from pooled studies and large clustered data sets (Q6628131) (← links)
- A tutorial on individualized treatment effect prediction from randomized trials with a binary endpoint (Q6628296) (← links)
- Minimum sample size for external validation of a clinical prediction model with a binary outcome (Q6628454) (← links)
- A two-stage prediction model for heterogeneous effects of treatments (Q6628471) (← links)
