A simple pooling method for variable selection in multiply imputed datasets outperformed complex methods
Abstract Background For the development of prognostic models, after multiple imputation, variable selection is advised to be applied from the pooled model. The aim of this study is to evaluate by using a simulation study and practical data example the performance of four different pooling methods fo...
Main Authors: | A. M. Panken, M. W. Heymans |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2022-08-01
|
Series: | BMC Medical Research Methodology |
Subjects: | |
Online Access: | https://doi.org/10.1186/s12874-022-01693-8 |
Similar Items
-
A joint use of pooling and imputation for genotyping SNPs
by: Camille Clouard, et al.
Published: (2022-10-01) -
A Safe-Region Imputation Method for Handling Medical Data with Missing Values
by: Shu-Fen Huang, et al.
Published: (2020-10-01) -
A comparison of imputation methods for categorical data
by: Shaheen MZ. Memon, et al.
Published: (2023-01-01) -
Selection of Variables that Influence Drug Injection in Prison: Comparison of Methods with Multiple Imputed Data Sets
by: Saiedeh Haji-Maghsoudi, et al.
Published: (2014-04-01) -
The Feature Selection Effect on Missing Value Imputation of Medical Datasets
by: Chia-Hui Liu, et al.
Published: (2020-03-01)