Evaluation of predictive model performance of an existing model in the presence of missing data
Author:
Affiliation:
1. Department of Biostatistics University of Michigan Ann Arbor Michigan USA
2. Department of Radiation Oncology University of Michigan Ann Arbor Michigan USA
3. Department of Urology Mayo Clinic Rochester Minnesota USA
Publisher
Wiley
Subject
Statistics and Probability,Epidemiology
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1002/sim.8978
Reference20 articles.
1. Assessing the Performance of Prediction Models
2. Statistical Analysis with Missing Data, Third Edition
3. The estimation and use of predictions for the assessment of model performance using large samples with multiply imputed data
4. Missing covariate data in medical research: To impute is better than to ignore
5. Review of inverse probability weighting for dealing with missing data
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1. Mallows model averaging based on kernel regression imputation with responses missing at random;Journal of Statistical Planning and Inference;2023-11
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