Statistics in Biosciences

356 papers and 2.5k indexed citations
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About

The 356 papers published in Statistics in Biosciences in the last decades have received a total of 2.5k indexed citations. Papers published in Statistics in Biosciences usually cover Statistics and Probability (197 papers), Molecular Biology (90 papers) and Economics and Econometrics (49 papers) specifically the topics of Statistical Methods and Inference (120 papers), Statistical Methods in Clinical Trials (89 papers) and Statistical Methods and Bayesian Inference (79 papers). The most active scholars publishing in Statistics in Biosciences are Hein Putter, Hans C. van Houwelingen, John D. Kalbfleisch, Robert A. Wolfe, Wei Sun, Yi‐Juan Hu, Lloyd E. Chambless, Ziding Feng, Jing Fan and Thomas Alexander Gerds.

In The Last Decade

Statistics in Biosciences

300 papers receiving 2.3k citations

Fields of papers published in Statistics in Biosciences

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Statistics in Biosciences. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Statistics in Biosciences.

Countries where authors publish in Statistics in Biosciences

Since Specialization
Citations

This map shows the geographic impact of research published in Statistics in Biosciences. 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 papers published in Statistics in Biosciences with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Statistics in Biosciences more than expected).

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.

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