GuidelineBMC medical research methodology2009
Combining estimates of interest in prognostic modelling studies after multiple imputation: current practice and guidelines.
Guideline in BMC medical research methodology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 449 papers, 4 of them syntheses that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
449 citing papers in PubMed, 4 syntheses or guidelines pooled it.
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- Safety of treating acute pulmonary embolism at home: an individual patient data meta-analysis.European heart journal · 2024Pooled it
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- Cost-Effectiveness of In-Bed Cycling and Routine Physiotherapy for Patients Receiving Mechanical Ventilation.JAMA network open · 2025Trial
- Adaptive interventions for alcohol misuse and violent behaviors among adolescents and emerging adults in the emergency department: Outcomes from a sequential multiple assignment randomized controlled trial.Drug and alcohol dependence · 2025Trial
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- Developing a prediction model for all-cause mortality risk among patients with type 2 diabetes mellitus in Shanghai, China.Journal of diabetes · 2023Trial
- A qEEG-based prognostic model for cognitive impairment after ischemic stroke: Development and internal validation.IBRO neuroscience reports · 2026Article
- School-Family Linked and Online-Offline Combined Tobacco Control Intervention for Adolescents: Protocol for a Cluster Randomized Pilot Trial.JMIR research protocols · 2026Article
- Association of baseline brain care score with the incidence of age-related eye diseases.Eye (London, England) · 2026Article
- The effect of SGLT2 inhibitors, GLP-1 receptor agonists, or DPP-4 inhibitors on stroke risk in type 2 diabetes: a nationwide longitudinal cohort study in Sweden with contextualisation analysis.EClinicalMedicine · 2026Article
- Evaluating discrimination of prediction models for recurrent clinical events.Diagnostic and prognostic research · 2026Article
- Multiple R1 margins are associated with shorter overall survival: national register-based study on pancreatic cancer.BJS open · 2026Article
- The Effect of Covariate Adjustment for Cox Regression in Cardiovascular Outcome Trials.Therapeutic innovation & regulatory science · 2026Article
389 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
backgroundMultiple imputation (MI) provides an effective approach to handle missing covariate data within prognostic modelling studies, as it can properly account for the missing data uncertainty. The multiply imputed datasets are each analysed using standard prognostic modelling techniques to obtain the estimates of interest. The estimates from each imputed dataset are then combined into one overall estimate and variance, incorporating both the within and between imputation variability. Rubin's rules for combining these multiply imputed estimates are based on asymptotic theory. The resulting combined estimates may be more accurate if the posterior distribution of the population parameter of interest is better approximated by the normal distribution. However, the normality assumption may not be appropriate for all the parameters of interest when analysing prognostic modelling studies, such as predicted survival probabilities and model performance measures.
methodsGuidelines for combining the estimates of interest when analysing prognostic modelling studies are provided. A literature review is performed to identify current practice for combining such estimates in prognostic modelling studies.
resultsMethods for combining all reported estimates after MI were not well reported in the current literature. Rubin's rules without applying any transformations were the standard approach used, when any method was stated.
conclusionThe proposed simple guidelines for combining estimates after MI may lead to a wider and more appropriate use of MI in future prognostic modelling studies.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.