Ajit C. Tamhane

117 papers receiving 5.0k citations

Hit Papers

Multiple Comparison Procedures1987202620002013198750010001.5k

Peers

Ajit C. Tamhane
Comparison fields: 5 of 210
  • Statistics and Probability 2.2k
  • Management Science and Operations Research 1.8k
  • Statistics, Probability and Uncertainty 686
  • Control and Systems Engineering 566
  • Artificial Intelligence 456
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Countries citing papers authored by Ajit C. Tamhane

Since Specialization
Citations

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

Fields of papers citing papers by Ajit C. Tamhane

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ajit C. Tamhane. 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 Ajit C. Tamhane. The network helps show where Ajit C. Tamhane may publish in the future.

Co-authorship network of co-authors of Ajit C. Tamhane

This figure shows the co-authorship network connecting the top 25 collaborators of Ajit C. Tamhane. A scholar is included among the top collaborators of Ajit C. Tamhane 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 Ajit C. Tamhane. Ajit C. Tamhane 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 49
3 11
4 96
5 16
6
Statistics and Data Analysis: From Elementary to Intermediate
228
7 52
8 181
9 13
10
Optimal Allocation of Observations in Subset Selection and Multiple Comparisons with a Control, and Associated Tables (With Application to Drug Screening)
0
11 1
12 96
13
Design of experiments : ranking and selection : essays in honor of Robert E. Bechhofer
12
14
Designing Experiments for Selecting a Normal Population with a Large Mean and a Small Variance,
1
15 10
16 15
17 70
18
Incomplete block designs for comparing treatments with a control (II): Optimal designs for p = 2(1)6; k = 2 and p = 3; k = 3
4
19 164
20 2

About Ajit C. Tamhane

Ajit C. Tamhane is a scholar working on Statistics and Probability, Management Science and Operations Research and Statistics, Probability and Uncertainty, having authored 121 papers that have together received 5.3k indexed citations. Recurring topics across this work include Optimal Experimental Design Methods (69 papers), Statistical Methods in Clinical Trials (58 papers) and Statistical Methods and Bayesian Inference (22 papers). The work is most often cited by research in Statistics and Probability (2.2k citations), Management Science and Operations Research (1.8k citations) and Statistics, Probability and Uncertainty (686 citations). Ajit C. Tamhane has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Yosef Hochberg, Charles W. Dunnett, Robert E. Bechhofer, Thomas J. Santner, Alex Dmitrienko, R.S.H. Mah, Dorothy D. Dunlop, Richard S. H. Mah, David Goldsman and Edward C. Malthouse. Their work appears in journals such as Journal of the American Statistical Association, Technometrics and Biometrics.

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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