ArticlePsychological methods2023
How to apply variable selection machine learning algorithms with multiply imputed data: A missing discussion.
Article in Psychological methods, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Parental anxiety in differences of sex development and hypospadias: a psychosocial characterization.Journal of the Endocrine Society · 2026Article
- How to apply Bayesian stochastic search variable selection with multiply imputed data.Psychological methods · 2026Article
- A novel context-discrepancy assessment of impression management facets in autistic and non-autistic adults: an initial validation.Molecular autism · 2026Article
- Early-life prediction of school-age asthma among recurrent Wheezers in preschoolers: The WHEEP study.Pediatric allergy and immunology : official publication of the European Society of Pediatric Allergy and Immunology · 2025Article
- Using Machine Learning to Identify Social Determinants of Health that Impact Discharge Disposition for Hospitalized Patients.Journal of the American Medical Directors Association · 2025Article
- Elucidating the role of peripheral monocyte nicotinic acetylcholine receptors and inflammation in cognitive outcomes in older adults.Biogerontology · 2025Article
- Problem of pain in the USA: evaluating the generalisability of high-impact chronic pain models over time using National Health Interview Survey (NHIS) data.BMJ public health · 2025Article
- Predictive model for genital tract infections among men and women in Ghana: An application of LASSO penalized cross-validation regression model.Epidemiology and infection · 2024Article
- Predicting the Performance of Students Using Deep Ensemble Learning.Journal of Intelligence · 2024Article
- Predicting implementation of response to intervention in math using elastic net logistic regression.Frontiers in psychology · 2024Article
- Electronic health records and stratified psychiatry: bridge to precision treatment?Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2024Review
- Clinical and high-resolution magnetic resonance imaging-based prediction of ischemic stroke in cervical artery dissection.Frontiers in neurologyArticle
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Authors and funding
4 authors.
Funding
Abstract
Psychological researchers often use standard linear regression to identify relevant predictors of an outcome of interest, but challenges emerge with incomplete data and growing numbers of candidate predictors. Regularization methods like the LASSO can reduce the risk of overfitting, increase model interpretability, and improve prediction in future samples; however, handling missing data when using regularization-based variable selection methods is complicated. Using listwise deletion or an ad hoc imputation strategy to deal with missing data when using regularization methods can lead to loss of precision, substantial bias, and a reduction in predictive ability. In this tutorial, we describe three approaches for fitting a LASSO when using multiple imputation to handle missing data and illustrate how to implement these approaches in practice with an applied example. We discuss implications of each approach and describe additional research that would help solidify recommendations for best practices. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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