ArticleThe Canadian journal of statistics = Revue canadienne de statistique2019
Synthetic data method to incorporate external information into a current study.
Article in The Canadian journal of statistics = Revue canadienne de statistique, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A meta-inference framework to integrate multiple external models into a current study.Biostatistics (Oxford, England) · 2023Pooled it
- ReFIT: Federated Transfer Learning for Sequential Prediction and Uncertainty Quantification Using Streaming EHR Data.Statistics in biosciences · 2026Article
- Mediation with External Summary Statistic Information.Biostatistics (Oxford, England) · 2025Article
- FairFML: fair federated machine learning with a case study on reducing gender disparities in cardiac arrest outcome prediction.npj health systems · 2025Article
- Article
- Improving prediction of linear regression models by integrating external information from heterogeneous populations: James-Stein estimators.Biometrics · 2024Article
- Robust data integration from multiple external sources for generalized linear models with binary outcomes.Biometrics · 2024Article
- A synthetic data integration framework to leverage external summary-level information from heterogeneous populations.Biometrics · 2023Article
- Improvement of an External Predictive Model Based on New Information Using a Synthetic Data Approach: Application to CADASIL.Neurology. Genetics · 2023Article
- Integrating Information from Existing Risk Prediction Models with No Model Details.The Canadian journal of statistics = Revue canadienne de statistique · 2023Article
- Data integration: exploiting ratios of parameter estimates from a reduced external model.Biometrika · 2023Article
- COMMUTE: Communication-efficient transfer learning for multi-site risk prediction.Journal of biomedical informatics · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
We consider the situation where there is a known regression model that can be used to predict an outcome, Y, from a set of predictor variables
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.