Georg Heinze
Statistics and Probability · 2002–2020
A researcher in the Science corpus: 4 papers; trusts 8 researchers and is trusted by 26 researchers here, as inferred from the citation graph.
Subfields
- Statistics and Probability — 43 citations into it; #2,016 of 12,932 by trust here, #2,800 by citations
- Artificial Intelligence — 35 citations into it
Whom Georg Heinze trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- H. V. van Houwelingen
- Jonathan E. Taylor
- Tyler J. VanderWeele
- Robert Tibshirani
- Willi Sauerbrei
- Leo Breiman
- Ilya Shpitser
- Saskia le Cessie
- Ewout W. Steyerberg
- Gary King
Who trusts Georg Heinze overall
- Ioannis Kosmidis
- Heng Lian
- Yingbo Li
- David Firth
- Tae-Hyoung Tommy Gim
- Mee Young Park
- B. L. Sargeant
- M. Pavlou
- A. Royo
- Johan A. Oldekop
Papers from Georg Heinze's perspective
Ordered by how strongly the researchers Georg Heinze trusts endorse each paper. Same corpus, a different order for every researcher.
- Estimating the Dimension of a Model
- Shrinkage and Penalized Likelihood as Methods to Improve Predictive Accuracy
- Statistical Modeling: The Two Cultures (with comments and a rejoinder by the author)
- Statistical learning and selective inference
- A weakly informative default prior distribution for logistic and other regression models
- A solution to the problem of separation in logistic regression (Statistics in Medicine)
- Regression Shrinkage and Selection via the Lasso
- Logistic Regression in Rare Events Data (Political Analysis)
- A new criterion for confounder selection
- Assessing the performance of prediction models: a framework for some traditional and novel measures (Epidemiology)
Their papers
- A solution to the problem of separation in logistic regression (2002) — 2,231 citations
- Firth's logistic regression with rare events: accurate effect estimates and predictions? (2017) — 391 citations
- Variable selection – A review and recommendations for the practicing statistician (2018) — 1,370 citations
- Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal (2020) — 2,435 citations