K. Abrams

Statistics and Probability · 2000–2016

A researcher in the Science corpus: 13 papers; trusts 14 researchers and is trusted by 14 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 71 citations into it; #4,815 of 12,932 by trust here, #347 by citations
• Economics and Econometrics — 17 citations into it
• Artificial Intelligence — 12 citations into it
• Surgery — 11 citations into it
• Endocrinology, Diabetes and Metabolism — 6 citations into it
• Probabilistic & Bayesian Methods — 6 citations into it

Whom K. Abrams trusts overall

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

1. A. Sutton
2. David J. Spiegelhalter
3. J. Sterne
4. Julian P. T. Higgins
5. N. Duan
6. Richard L. Tweedie
7. Denise Draper
8. Douglas G. Altman
9. N. Terrin
10. Matthias Egger

Who trusts K. Abrams overall

1. Brian H Neelon
2. T. Jess
3. Quentin F. Gronau
4. B. Mihaylova
5. Lifeng Lin
6. Linyu Shi

Papers from K. Abrams's perspective

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

1. Controlling the risk of spurious findings from meta‐regression (Statistics in Medicine)
2. General methods for monitoring convergence of iterative simulations
3. BUGS - Bayesian inference Using Gibbs Sampling Version 0.50
4. A Nonparametric “Trim and Fill” Method of Accounting for Publication Bias in Meta-Analysis
5. Trim and Fill: A Simple Funnel‐Plot–Based Method of Testing and Adjusting for Publication Bias in Meta‐Analysis (Biometrics)
6. Methods for Meta-Analysis in Medical Research
7. Assessment and Propagation of Model Uncertainty
8. Smearing Estimate: A Nonparametric Retransformation Method
9. Multilevel Statistical Models
10. Performance of the trim and fill method in the presence of publication bias and between‐study heterogeneity (Statistics in Medicine)

Their papers

• How vague is vague? A simulation study of the impact of the use of vague prior distributions in MCMC using WinBUGS (2005) — 533 citations
• Prognosis Research Strategy (PROGRESS) 2: Prognostic Factor Research (2013) — 748 citations
• Predicting costs over time using Bayesian Markov chain Monte Carlo methods: an application to early inflammatory polyarthritis. (2007) — 54 citations
• Prognosis research strategy (PROGRESS) 1: A framework for researching clinical outcomes (2013) — 596 citations
• Empirical assessment of effect of publication bias on meta-analyses (2000) — 1,399 citations
• Contour-enhanced meta-analysis funnel plots help distinguish publication bias from other causes of asymmetry. (2008) — 1,832 citations
• Performance of the trim and fill method in the presence of publication bias and between‐study heterogeneity (2007) — 688 citations
• Comparison of two methods to detect publication bias in meta-analysis. (2006) — 2,094 citations
• Bayesian methods in meta-analysis and evidence synthesis. (2001) — 445 citations
• Use of Bayesian Markov Chain Monte Carlo Methods to Model Cost-of-Illness Data (2003) — 36 citations
• NICE DSU Technical Support Document 18: Methods for population-adjusted indirect comparisons in submissions to NICE (2016) — 330 citations
• Pharmacological and lifestyle interventions to prevent or delay type 2 diabetes in people with impaired glucose tolerance: systematic review and meta-analysis (2007) — 1,199 citations
• The risk of colorectal cancer in ulcerative colitis: a meta-analysis (2001) — 3,000 citations