Daniel Jurich

24 papers receiving 332 citations

Peers

Daniel Jurich
Comparison fields: 5 of 60
  • Health Informatics 28
  • Family Practice 21
  • Management Science and Operations Research 50
  • Social Psychology 67
  • Statistics and Probability 27
Replace Kimberly A. Swygert with:
Kimberly A. Swygert United States
Chi Chang United States
Maria Kambouri United Kingdom
Michael Parker United Kingdom
Christine Brown Australia
Aurélien Allard Switzerland
Chad W. Buckendahl United States
Jason P. Kopp United States
Chinthaka Balasooriya Australia
Sen‐Chi Yu Taiwan
Daniel Jurich relative to Kimberly A. Swygert United States Kimberly A. Swygert's profile →
Citations per field
00.5×4.5×
Kimberly A. Swygert · 1×
Citations per year

Countries citing papers authored by Daniel Jurich

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Jurich

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011110
2 201731
3 202329
4 201827
5 201327
6 202024
7 201917
8 201216
9 201814
10 202111
11 202111
12 20148
13 20208
14 20226
15 20123
16 20233
17 20213
18 20182
19 20122
20 20232

About Daniel Jurich

Daniel Jurich is a scholar working on Management Science and Operations Research, Computer Networks and Communications, Statistics and Probability, Public Health, Environmental and Occupational Health and Experimental and Cognitive Psychology, having authored 28 papers that have together received 358 indexed citations. Recurring topics across this work include Psychometric Methodologies and Testing (10 papers), Advanced Statistical Modeling Techniques (7 papers), Advanced Statistical Methods and Models (4 papers), Innovations in Medical Education (3 papers), Reliability and Agreement in Measurement (2 papers), Disability Education and Employment (1 paper), Statistics Education and Methodologies (1 paper) and Behavioral and Psychological Studies (1 paper). The work is most often cited by research in Health Informatics (28 citations), Family Practice (21 citations), Management Science and Operations Research (50 citations), Social Psychology (67 citations) and Statistics and Probability (27 citations). Daniel Jurich has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Tracy E. Zinn, Jason P. Kopp, Sara J. Finney, Richard A. Feinberg, Laine Bradshaw, Miguel Paniagua, Christine E. DeMars, Sally A. Santen, Brian E. Clauser and Michael Barone. Their work appears in journals such as Academic Medicine, Applied Psychological Measurement, Applied Measurement in Education, Innovative Higher Education and Journal of Veterinary Medical Education.

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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