LASSO-Based Survival Prediction Modeling with Multiply Imputed Data: A Case Study in Tuberculosis Mortality Prediction.

Using health administrative datasets for developing prediction models is always challenging due to missing values in key predictors. Multiple imputation has been recommended to deal with missing predictor values. However, predicting survival outcomes using regularized regression, for example, Cox-LA...

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Detalles Bibliográficos

Publicado en:	American Statistician Vol. 80; no. 1; pp. 77 - 89
Autores principales:	Hossain, Md. Belal, Sadatsafavi, Mohsen, Johnston, James C., Wong, Hubert, Cook, Victoria J., Karim, Mohammad Ehsanul
Formato:	Artículo
Publicado:	Taylor & Francis Ltd Feb2026
Materias:	Multiple imputation (Statistics) Tuberculosis mortality Survival analysis (Biometry) Regression analysis Statistical models Proportional hazards models Regularization parameter
Acceso en línea:	Ver este registro en EBSCOhost