ArticleJournal of the American Statistical Association2020
Improved small-sample estimation of nonlinear cross-validated prediction metrics.
Article in Journal of the American Statistical Association, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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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.
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Who cites it
11 citing papers in PubMed.
- Personalized azithromycin treatment rules for children with watery diarrhea using machine learning.Nature communications · 2025Trial
- Beta cell microRNAs function as molecular hubs of type 1 diabetes pathogenesis and as biomarkers of diabetes risk.Diabetologia · 2026Article
- The Authors Respond.Epidemiology (Cambridge, Mass.) · 2025Article
- Cross-validation: what does it estimate and how well does it do it?Journal of the American Statistical Association · 2024Article
- Application of the SLAPNAP statistical learning tool to broadly neutralizing antibody HIV prevention research.iScience · 2023Article
- A Guide to Cross-Validation for Artificial Intelligence in Medical Imaging.Radiology. Artificial intelligence · 2023Review
- A two-stage super learner for healthcare expenditures.Health services & outcomes research methodology · 2022Article
- Accounting for motion in resting-state fMRI: What part of the spectrum are we characterizing in autism spectrum disorder?NeuroImage · 2022Article
- Testing a global null hypothesis using ensemble machine learning methods.Statistics in medicine · 2022Article
- Super LeArner Prediction of NAb Panels (SLAPNAP): a containerized tool for predicting combination monoclonal broadly neutralizing antibody sensitivity.Bioinformatics (Oxford, England) · 2021Article
- Cross-Validation of Predictive Equation for Cardiorespiratory Fitness by Modified Shuttle Walk Test in Adults with Schizophrenia: A Secondary Analysis of the CORTEX-SP Study.International journal of environmental research and public health · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
When predicting an outcome is the scientific goal, one must decide on a metric by which to evaluate the quality of predictions. We consider the problem of measuring the performance of a prediction algorithm with the same data that were used to train the algorithm. Typical approaches involve bootstrapping or cross-validation. However, we demonstrate that bootstrap-based approaches often fail and standard cross-validation estimators may perform poorly. We provide a general study of cross-validation-based estimators that highlights the source of this poor performance, and propose an alternative framework for estimation using techniques from the efficiency theory literature. We provide a theorem establishing the weak convergence of our estimators. The general theorem is applied in detail to two specific examples and we discuss possible extensions to other parameters of interest. For the two explicit examples that we consider, our estimators demonstrate remarkable finite-sample improvements over standard approaches.
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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.