Johannes B Reitsma

Statistics and Probability · 2003–2024

A researcher in the Science corpus: 29 papers; trusts 55 researchers and is trusted by 19 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 359 citations into it; #2,739 of 12,932 by trust here, #230 by citations
• Economics and Econometrics — 130 citations into it; #7,312 of 23,481 by trust here, #1,248 by citations
• Cardiology and Cardiovascular Medicine — 110 citations into it
• General Health Professions — 97 citations into it; #1,839 of 4,781 by trust here, #228 by citations
• Epidemiology — 96 citations into it
• Artificial Intelligence — 81 citations into it
• Public Health, Environmental and Occupational Health — 77 citations into it
• Surgery — 59 citations into it

Whom Johannes B Reitsma trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Karel G. M. Moons
2. Douglas G. Altman
3. Patrick Royston
4. Patrick M. M. Bossuyt
5. Y. Vergouwe
6. David Moher
7. Ewout W. Steyerberg
8. Gary S. Collins
9. J. Deeks
10. for the Statistics Subcommittee of the NCI—EORTC Worki Diagnostics

Who trusts Johannes B Reitsma overall

1. R. Riley
2. Gary S. Collins
3. R. Harbord
4. Karel G. M. Moons
5. Douglas G. Altman
6. S. Gilbody
7. Patrick M. M. Bossuyt
8. David Moher
9. A. Rutjes
10. J. Deeks

Papers from Johannes B Reitsma's perspective

Ordered by how strongly the researchers Johannes B Reitsma trusts endorse each paper. Same corpus, a different order for every researcher.

1. Strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies (British medical journal)
2. Regression Modeling Strategies (Technometrics)
3. Sources of Variation and Bias in Studies of Diagnostic Accuracy (Annals of Internal Medicine)
4. Updating methods improved the performance of a clinical prediction model in new patients. (Journal of Clinical Epidemiology)
5. Multiple imputation using chained equations: Issues and guidance for practice (Statistics in Medicine)
6. The Revised CONSORT Statement for Reporting Randomized Trials: Explanation and Elaboration (Annals of Internal Medicine)
7. Evaluation of the Quality of Prognosis Studies in Systematic Reviews (Annals of Internal Medicine)
8. Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers (Statistics in Medicine)
9. Risk prediction models: II. External validation, model updating, and impact assessment (Heart)
10. Prognosis Research Strategy (PROGRESS) 2: Prognostic Factor Research (PLoS Medicine)

Their papers

• Bivariate analysis of sensitivity and specificity produces informative summary measures in diagnostic reviews. (2005) — 3,200 citations
• The STARD statement for reporting studies of diagnostic accuracy: explanation and elaboration. (2003) — 791 citations
• The STARD Statement for Reporting Studies of Diagnostic Accuracy: Explanation and Elaboration (2003) — 1,546 citations
• Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): The TRIPOD statement (2015) — 894 citations
• Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): Explanation and Elaboration (2015) — 4,311 citations
• Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement (2015) — 2,276 citations
• Sources of Variation and Bias in Studies of Diagnostic Accuracy (2004) — 836 citations
• A review of solutions for diagnostic accuracy studies with an imperfect or missing reference standard. (2009) — 386 citations
• Evidence of bias and variation in diagnostic accuracy studies (2006) — 635 citations
• Calculating the sample size required for developing a clinical prediction model (2020) — 2,194 citations
• Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies: The CHARMS Checklist (2014) — 1,708 citations
• STARD 2015: an updated list of essential items for reporting diagnostic accuracy studies (2015) — 3,489 citations
• PROBAST: A Tool to Assess the Risk of Bias and Applicability of Prediction Model Studies (2019) — 2,019 citations
• Get real in individual participant data (IPD) meta‐analysis: a review of the methodology (2015) — 307 citations
• Sample size for binary logistic prediction models: Beyond events per variable criteria (2018) — 679 citations
• PROBAST: A Tool to Assess Risk of Bias and Applicability of Prediction Model Studies: Explanation and Elaboration (2019) — 1,227 citations
• Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD Statement (2015) — 368 citations
• Protocol for development of a reporting guideline (TRIPOD-AI) and risk of bias tool (PROBAST-AI) for diagnostic and prognostic prediction model studies based on artificial intelligence (2021) — 676 citations
• Transparent reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): the TRIPOD statement. (2015) — 1,177 citations
• Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): The TRIPOD Statement (2015) — 899 citations