Martin Hecht

76 papers receiving 1.1k citations

Peers

Martin Hecht
Comparison fields: 5 of 139
  • Statistics and Probability 155
  • Experimental and Cognitive Psychology 227
  • Management Science and Operations Research 186
  • Applied Psychology 76
  • Family Practice 32
Replace Florian Naudet with:
Florian Naudet France
George Karabatsos United States
Pasquale Anselmi Italy
Gilles Dutilh Switzerland
Michael R. Dougherty United States
York Hagmayer Germany
Frank Rijmen United States
David Magis Belgium
Takahiro Hoshino Japan
Richard A. Carlson United States
Martin Hecht relative to Florian Naudet France Florian Naudet's profile →
Citations per field
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Citations per year

Countries citing papers authored by Martin Hecht

Since Specialization
Citations

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

Fields of papers citing papers by Martin Hecht

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 78 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201980
2 200762
3 200559
4 202048
5 200547
6 201647
7 201344
8 202043
9 202235
10 200734
11 201531
12 202129
13 202328
14 202427
15 201427
16 201925
17 201324
18 202122
19 201421
20 202020

About Martin Hecht

Martin Hecht is a scholar working on Statistics and Probability, Management Science and Operations Research, Experimental and Cognitive Psychology, Clinical Psychology and Artificial Intelligence, having authored 78 papers that have together received 1.2k indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (17 papers), Psychometric Methodologies and Testing (12 papers), Mental Health Research Topics (11 papers), Statistical Methods and Inference (9 papers), Behavioral Health and Interventions (6 papers), Advanced Statistical Modeling Techniques (6 papers), COVID-19 and Mental Health (6 papers) and Innovations in Medical Education (5 papers). The work is most often cited by research in Statistics and Probability (155 citations), Experimental and Cognitive Psychology (227 citations), Management Science and Operations Research (186 citations), Applied Psychology (76 citations) and Family Practice (32 citations). Martin Hecht has collaborated with scholars based in Germany, Norway and United States. Frequent co-authors include Steffen Zitzmann, Manuel C. Voelkle, Stefan K. Schauber, Zineb Miriam Nouns, Tania Singer, Sarita Silveira, Oliver Lüdtke, Alexander Robitzsch, Adriano Chiò and Michael Swash. Their work appears in journals such as Structural Equation Modeling A Multidisciplinary Journal, Large-scale Assessments in Education, Educational and Psychological Measurement, Advances in Health Sciences Education and International Journal of Environmental Research and Public Health.

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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