ArticlePopulation health metrics2024
The impact of different imputation methods on estimates and model performance: an example using a risk prediction model for premature mortality.
Article in Population health metrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- PneumoScore: Risk Prediction Model for 90-Day Mortality After Lung Resection.Annals of surgical oncology · 2026Observational
- Back-to-base Versus In-transit Machine Perfusion in Donation After Circulatory Death Liver Transplantation: Insights From a National Registry.Transplantation direct · 2026Article
- A study protocol for a predictive model to assess population‑based risk of adverse pregnancy outcomes: The Adverse Pregnancy Outcomes Population Risk Tool (PregPoRT).Diagnostic and prognostic research · 2026Review
- Menopausal hormone therapy and long term mortality: nationwide, register based cohort study.BMJ (Clinical research ed.) · 2026Article
- Associations between monthly temperature anomalies and mortality among children younger than five years in low- and middle-income countries.Communications medicine · 2025Article
- Predicting hospital admissions, ICU utilization, and prolonged length of stay among febrile pediatric emergency department patients using incomplete and imbalanced electronic health record (EHR) data strategies.International journal of medical informatics · 2025Article
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Authors and funding
5 authors.
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Abstract
objectiveTo compare how different imputation methods affect the estimates and performance of a prediction model for premature mortality. STUDY DESIGN AND
settingSex-specific Weibull accelerated failure time survival models were run on four separate datasets using complete case, mode, single and multiple imputation to impute missing values. Six performance measures were compared to access predictive accuracy (Nagelkerke R
resultsThe highest proportion of missingness for a single variable was 10.86% for the female model and 8.24% for the male model. Comparing the performance measures for complete case, mode, single and multiple imputation: the Nagelkerke R
conclusionIn the scenarios examined in this study, mode imputation performed well when using a population health survey compared to single and multiple imputation when predictive performance measures is the main model goal. To generate unbiased hazard ratios, multiple imputation methods were superior. This study shows the need to consider the best imputation approach for a predictive model development given the conditions of missing data and the goals of the analysis.
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