Jeff Maca

926 citations
16 papers · 525 indexed · h-index 8

Jeff Maca

14 papers receiving 498 citations

Peers

Jeff Maca
Comparison fields: 5 of 64
  • Transplantation 203
  • Statistics and Probability 237
  • Statistics, Probability and Uncertainty 69
  • Psychiatry and Mental health 113
  • Management Science and Operations Research 84
Replace Gaohong Dong with:
Gaohong Dong United States
Étienne Dantan France
Yuping Dong United States
Sarah Goring United States
Jérémie Gras Belgium
L. Esserman United States
Kinjal Sanghavi United States
Michael D. deB. Edwardes Canada
Dankward Kodlin United States
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Citations per field
00.5×3.6×
Gaohong Dong · 1×
Citations per year

Countries citing papers authored by Jeff Maca

Since Specialization
Citations

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

Fields of papers citing papers by Jeff Maca

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Jeff Maca, 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 Jeff Maca Line = papers co-authored together Jeff Maca links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 202416
2 20220
3 20181
4 20181
5 20173
6 20166
7 20167
8 20156
9 201311
10 201315
11 201044
12 200963
13 20070
14 200687
15 2004243
16 200222

About Jeff Maca

Jeff Maca is a scholar working on Statistics and Probability, Transplantation, Statistics, Probability and Uncertainty, Management Science and Operations Research and Economics and Econometrics, having authored 16 papers that have together received 525 indexed citations. Recurring topics across this work include Statistical Methods in Clinical Trials (13 papers), Health Systems, Economic Evaluations, Quality of Life (6 papers), Biosimilars and Bioanalytical Methods (3 papers), Optimal Experimental Design Methods (3 papers), Meta-analysis and systematic reviews (2 papers), Diabetes Treatment and Management (2 papers), Cancer Genomics and Diagnostics (2 papers) and Pharmaceutical studies and practices (2 papers). The work is most often cited by research in Transplantation (203 citations), Statistics and Probability (237 citations), Statistics, Probability and Uncertainty (69 citations), Psychiatry and Mental health (113 citations) and Management Science and Operations Research (84 citations). Jeff Maca has collaborated with scholars based in United States, Switzerland and United Kingdom. Frequent co-authors include Michael Krams, Angelo de Mattos, Hans W. Sollinger, Wolfgang Arns, Michael Hall, Maurizio Salvadori, Federico Oppenheimer, Herwig Holzer, Paul Gallo and Vladimir Dragalin. Their work appears in journals such as Therapeutic Innovation & Regulatory Science, Statistics in Biopharmaceutical Research, Drug Information Journal, Journal of Biopharmaceutical Statistics 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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