Thomas Jaki

28.8k citations
175 papers · 2.9k · 1 hit paper · h-index 29

Impact in

Papers in

Thomas Jaki

159 papers receiving 2.9k citations

Thomas Jaki's Hit Papers

Adaptive designs in clinical trials: why use them, and how to run and report them 2018 · 439 citations
4390+2+5Years since publication100200300400

Peers

Thomas Jaki
Comparison fields: 5 of 173
  • Statistics and Probability 1.4k
  • Management Science and Operations Research 531
  • Statistics, Probability and Uncertainty 174
  • Economics and Econometrics 440
  • Health Informatics 16
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Thomas Jaki relative to Adrian Mander United Kingdom Adrian Mander's profile →
Citations per field
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Adrian Mander · 1×
Citations per year

Countries citing papers authored by Thomas Jaki

Since Specialization
Citations

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

Fields of papers citing papers by Thomas Jaki

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Thomas Jaki. 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 Thomas Jaki. The network helps show where Thomas Jaki may publish in the future.

Co-authors

The 25 scholars most cited alongside Thomas Jaki, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Thomas Jaki Line = papers co-authored together Thomas Jaki links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 175 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Adaptive designs in clinical trials: why use them, and how to run and report them
Hit paper breakdown →
2018439
2 201696
3 201295
4 202078
5 201273
6 201269
7 202064
8 201063
9 200957
10 200956
11 201954
12 201654
13 201249
14 202049
15 201646
16 201641
17 201339
18 201938
19 201635
20 201635

About Thomas Jaki

Thomas Jaki is a scholar working on Statistics and Probability, Management Science and Operations Research, Economics and Econometrics, Immunology and Molecular Biology, having authored 175 papers that have together received 2.9k indexed citations. Recurring topics across this work include Statistical Methods in Clinical Trials (116 papers), Optimal Experimental Design Methods (59 papers), Health Systems, Economic Evaluations, Quality of Life (35 papers), Statistical Methods and Bayesian Inference (25 papers), Advanced Causal Inference Techniques (22 papers), Statistical Methods and Inference (21 papers), Biosimilars and Bioanalytical Methods (21 papers) and Computational Drug Discovery Methods (11 papers). The work is most often cited by research in Statistics and Probability (1.4k citations), Management Science and Operations Research (531 citations), Statistics, Probability and Uncertainty (174 citations), Economics and Econometrics (440 citations) and Health Informatics (16 citations). Thomas Jaki has collaborated with scholars based in United Kingdom, Germany and United States. Frequent co-authors include James Wason, Martin J. Wolfsegger, Dominic Magirr, Philip Pallmann, John Whitehead, Christopher J. Weir, Munyaradzi Dimairo, Lisa V. Hampson, Adrian Mander and Matthew Sperrin. Their work appears in journals such as Statistics in Medicine, Statistical Methods in Medical Research, Pharmaceutical Statistics, Statistics in Biopharmaceutical Research and Clinical Trials.

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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