Practical recommendations for reportingFine‐Gray model analyses for competing risk data

728 indexed citations

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This paper, published in 2017, received 728 indexed citations. Written by Peter C. Austin and Jason P. Fine covering the research area of Economics and Econometrics and Statistics and Probability. It is primarily cited by scholars working on Cardiology and Cardiovascular Medicine (149 citations), Epidemiology (148 citations) and Surgery (141 citations). Published in Statistics in Medicine.

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doi.org/10.1002/sim.7501 →

Countries where authors are citing Practical recommendations for reportingFine‐Gray model analyses for competing risk data

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This map shows the geographic impact of Practical recommendations for reportingFine‐Gray model analyses for competing risk data. 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 Practical recommendations for reportingFine‐Gray model analyses for competing risk data with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Practical recommendations for reportingFine‐Gray model analyses for competing risk data more than expected).

Fields of papers citing Practical recommendations for reportingFine‐Gray model analyses for competing risk data

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Practical recommendations for reportingFine‐Gray model analyses for competing risk data. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Practical recommendations for reportingFine‐Gray model analyses for competing risk data.

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.

This paper is also available at doi.org/10.1002/sim.7501.

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