Journal article
A Simple Aggregation Rule for Penalized Regression Coefficients after Multiple Imputation
Journal of data science, Vol.19(1), pp.1-14
2021
DOI: 10.6339/21-JDS995
Abstract
Early in the course of the pandemic in Colorado, researchers wished to fit a sparse predictive model to intubation status for newly admitted patients. Unfortunately, the training data had considerable missingness which complicated the modeling process. I developed a quick solution to this problem: Median Aggregation of penaLized Coefficients after Multiple imputation (MALCoM). This fast, simple solution proved successful on a prospective validation set. In this manuscript, I show how MALCoM performs comparably to a popular alternative (MI-lasso), and can be implemented in more general penalized regression settings. A simulation study and application to local COVID-19 data is included.
Details
- Title: Subtitle
- A Simple Aggregation Rule for Penalized Regression Coefficients after Multiple Imputation
- Creators
- Ryan A. Peterson
- Resource Type
- Journal article
- Publication Details
- Journal of data science, Vol.19(1), pp.1-14
- DOI
- 10.6339/21-JDS995
- ISSN
- 1680-743X
- eISSN
- 1683-8602
- Number of pages
- 14
- Language
- English
- Date published
- 2021
- Academic Unit
- Biostatistics; Internal Medicine
- Record Identifier
- 9984914016602771
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