Andrew J. Vickers
Statistics and Probability · 2001–2019
A researcher in the Science corpus: 14 papers; trusts 5 researchers and is trusted by 27 researchers here, as inferred from the citation graph.
Subfields
- Statistics and Probability — 89 citations into it; #3,381 of 12,932 by trust here, #867 by citations
- Cardiology and Cardiovascular Medicine — 32 citations into it
- Economics and Econometrics — 32 citations into it; #6,268 of 23,481 by trust here, #2,262 by citations
- Epidemiology — 31 citations into it
- Artificial Intelligence — 14 citations into it
- Endocrinology, Diabetes and Metabolism — 12 citations into it
- Genetics — 7 citations into it
- Management Information Systems — 5 citations into it
Whom Andrew J. Vickers trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Nancy R. Cook
- Ewout W. Steyerberg
- Sunil Rao
- Mithat Gonen
- Michael J. Pencina
- Patrick J. Heagerty
- L. Chambless
Who trusts Andrew J. Vickers overall
- Ewout W. Steyerberg
- R. Riley
- B. Van calster
- Gary S. Collins
- Michael J. Pencina
- Benjamin Alan Goldstein
- E. Núñez
- Silvia Collado
- F. Egger
- Karel G. M. Moons
Papers from Andrew J. Vickers's perspective
Ordered by how strongly the researchers Andrew J. Vickers trusts endorse each paper. Same corpus, a different order for every researcher.
- Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis
- Limitations of the odds ratio in gauging the performance of a diagnostic, prognostic, or screening marker. (American Journal of Epidemiology)
- Evaluating the added predictive ability of a new marker: From area under the ROC curve to reclassification and beyond (Statistics in Medicine)
- What do we mean by validating a prognostic model? (Statistics in Medicine)
- Clinical Prediction Models—a Practical Approach to Development, Validation and Updating
- Estimation of time‐dependent area under the ROC curve for long‐term risk prediction (Statistics in Medicine)
- Statistical evaluation of prognostic versus diagnostic models: beyond the ROC curve. (Clinical Chemistry)
- Survival Model Predictive Accuracy and ROC Curves (Biometrics)
- Concordance probability and discriminatory power in proportional hazards regression
- Receiver operating characteristic curves and their use in radiology. (Radiology)
Their papers
- Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): Explanation and Elaboration (2015) — 4,311 citations
- Assessing the performance of prediction models: a framework for some traditional and novel measures (2010) — 4,522 citations
- Net benefit approaches to the evaluation of prediction models, molecular markers, and diagnostic tests (2016) — 1,011 citations
- Analysing controlled trials with baseline and follow up measurements (2001) — 2,065 citations
- Calibration: the Achilles heel of predictive analytics (2019) — 1,657 citations
- A simple, step-by-step guide to interpreting decision curve analysis (2019) — 915 citations
- Reporting and Interpreting Decision Curve Analysis: A Guide for Investigators (2018) — 1,022 citations
- Acupuncture for chronic pain: update of an individual patient data meta-analysis (2017) — 744 citations
- A Contemporary Prostate Cancer Grading System: A Validated Alternative to the Gleason Score (2015) — 1,333 citations
- Acupuncture for chronic pain: individual patient data meta-analysis (2012) — 937 citations
- What is a p-value anyway? 34 Stories to Help You Actually Understand Statistics (2009) — 50 citations
- Prostate-specific antigen and prostate cancer: prediction, detection and monitoring (2008) — 906 citations
- Chronic kidney disease after nephrectomy in patients with renal cortical tumours: a retrospective cohort study. (2006) — 1,549 citations
- Decision Curve Analysis: A Novel Method for Evaluating Prediction Models (2006) — 4,610 citations