David R. Bickel

1.4k citations
90 papers · 934 indexed · h-index 15
Topics
Statistical Methods in Clinical Trials (26 papers)Statistical Methods and Bayesian Inference (25 papers)Gene expression and cancer classification (21 papers)

In The Last Decade

David R. Bickel

84 papers receiving 900 citations

Peers

David R. Bickel
Comparison fields: 5 of 141
  • Statistics and Probability 363
  • Molecular Biology 309
  • Artificial Intelligence 187
  • Genetics 132
  • Statistics, Probability and Uncertainty 92
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Citations per field
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Citations per year

Countries citing papers authored by David R. Bickel

Since Specialization
Citations

This map shows the geographic impact of David R. Bickel'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 David R. Bickel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David R. Bickel more than expected).

Fields of papers citing papers by David R. Bickel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David R. Bickel. 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 David R. Bickel. The network helps show where David R. Bickel may publish in the future.

Co-authorship network of co-authors of David R. Bickel

This figure shows the co-authorship network connecting the top 25 collaborators of David R. Bickel. A scholar is included among the top collaborators of David R. Bickel 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 David R. Bickel. David R. Bickel is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 0
3 1
4 1
5 7
6 13
7 14
8 11
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10 4
11
Incorporating expert knowledge into frequentist results by combining subjective prior and objective posterior distributions: A generalization of confidence distribution combination
1
12
Degrees of Differential Gene Expression
1
13 36
14 10
15 41
16
Error-rate and decision-theoretic methods of multiple testing: Alternatives to controling conventional false discovery rates, with an application to microarrays
1
17
Selecting an Optimal Rejection Region for Multiple Testing: A decision theory alternative to FDR control, with an application to microarrays
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18 11
19 1
20 11

About David R. Bickel

David R. Bickel is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Statistical and Nonlinear Physics, having authored 90 papers that have together received 934 indexed citations. Recurring topics across this work include Statistical Methods in Clinical Trials (26 papers), Statistical Methods and Bayesian Inference (25 papers) and Gene expression and cancer classification (21 papers). The work is most often cited by research in Statistics and Probability (363 citations), Statistics, Probability and Uncertainty (92 citations) and Management Science and Operations Research (78 citations). David R. Bickel has collaborated with scholars based in Canada, United States and Austria. Frequent co-authors include R. Frühwirth, Bruce J. West, Bin Hu, Mei Guo, O. S. Smith, Mary A. Rupe, Erin L. Seifert, Véronic Bézaire, Sean H. Adams and Oliver Fiehn. Their work appears in journals such as Bioinformatics, PLoS ONE and The FASEB Journal.

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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