John D. Kalbfleisch
- Statistics and Probability top 0.01%
- Epidemiology top 0.2%
- Hepatology top 0.1%
- Economics and Econometrics top 0.2%
- Artificial Intelligence top 0.5%
- Co-authors
- Ross L. PrenticeMurray AitkinJerald F. LawlessAnna S. LokJoel K. GreensonHari S. ConjeevaramChun‐Tao WaiJorge A. Marrero
- Topics
- Statistical Methods and Bayesian Inference (52 papers)Statistical Methods and Inference (47 papers)Statistical Distribution Estimation and Applications (26 papers)
- Partner nations
- United StatesCanadaSingapore
In The Last Decade
John D. Kalbfleisch
142 papers receiving 22.4k citations
Hit Papers
Peers
Comparison fields: 5 of 219
- Statistics and Probability 8.3k
- Epidemiology 4.5k
- Hepatology 3.3k
- Economics and Econometrics 2.6k
- Artificial Intelligence 2.0k
Countries citing papers authored by John D. Kalbfleisch
This map shows the geographic impact of John D. Kalbfleisch's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by John D. Kalbfleisch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John D. Kalbfleisch more than expected).
Fields of papers citing papers by John D. Kalbfleisch
This network shows the impact of papers produced by John D. Kalbfleisch. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by John D. Kalbfleisch. The network helps show where John D. Kalbfleisch may publish in the future.
Co-authorship network of co-authors of John D. Kalbfleisch
This figure shows the co-authorship network connecting the top 25 collaborators of John D. Kalbfleisch. A scholar is included among the top collaborators of John D. Kalbfleisch based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with John D. Kalbfleisch. John D. Kalbfleisch is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 46 | |
| 3 | 4 | |
| 4 | 4 | |
| 5 | 25 | |
| 6 | 7 | |
| 7 | 3 | |
| 8 | 16 | |
| 9 | 17 | |
| 10 | 6 | |
| 11 | 129 | |
| 12 | 53 | |
| 13 | 86 | |
| 14 | 16 | |
| 15 | MODIFIED LIKELIHOOD RATIO TEST FOR HOMOGENEITY IN A TWO-SAMPLE PROBLEM | 5 |
| 16 | 34 | |
| 17 | Testing for homogeneity in genetic linkage analysis | 9 |
| 18 | The Statistical Analysis of Failure Time Databreakdown → | 2266 |
| 19 | 35 | |
| 20 | 290 |
About John D. Kalbfleisch
John D. Kalbfleisch is a scholar working on Statistics and Probability, Transplantation and Statistics, Probability and Uncertainty, having authored 143 papers that have together received 24.1k indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (52 papers), Statistical Methods and Inference (47 papers) and Statistical Distribution Estimation and Applications (26 papers). The work is most often cited by research in Statistics and Probability (8.3k citations), Hepatology (3.3k citations) and Transplantation (525 citations). John D. Kalbfleisch has collaborated with scholars based in United States, Canada and Singapore. Frequent co-authors include Ross L. Prentice, Murray Aitkin, Jerald F. Lawless, Anna S. Lok, Joel K. Greenson, Hari S. Conjeevaram, Chun‐Tao Wai, Jorge A. Marrero, Robert J. Fontana and John Neuhaus. Their work appears in journals such as Journal of the American Statistical Association, Hepatology and Technometrics.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.