Daniel Jurich

23 papers receiving 321 citations

Peers

Daniel Jurich
Comparison fields: 5 of 66
  • Health Informatics 29
  • Family Practice 29
  • Gender Studies 48
  • Management Science and Operations Research 49
  • Public Health, Environmental and Occupational Health 115
Replace Kimberly A. Swygert with:
Kimberly A. Swygert United States
Chi Chang United States
Wendy C. Cox United States
Kayley Lyons Australia
Jason P. Kopp United States
Denise Stockley Canada
Maria Kambouri United Kingdom
Yulia A. Strekalova United States
Carl J. Sheperis United States
Jay Blanchard United States
Daniel Jurich relative to Kimberly A. Swygert United States Kimberly A. Swygert's profile →
Citations per field
00.5×1.5×2.2×
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 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011109
2 201730
3 201827
4 201327
5 202325
6 202023
7 201917
8 201215
9 201814
10 202111
11 202111
12 20208
13 20148
14 20225
15 20123
16 20213
17 20232
18 20182
19 20122
20 20232

About Daniel Jurich

Daniel Jurich is a scholar working on Management Science and Operations Research, Public Health, Environmental and Occupational Health, Computer Networks and Communications, Gender Studies and Statistics and Probability, having authored 27 papers that have together received 347 indexed citations. Recurring topics across this work include Psychometric Methodologies and Testing (10 papers), Innovations in Medical Education (8 papers), Medical Education and Admissions (7 papers), Advanced Statistical Modeling Techniques (7 papers), Diversity and Career in Medicine (6 papers), Advanced Statistical Methods and Models (4 papers), Healthcare Policy and Management (2 papers) and Radiology practices and education (2 papers). The work is most often cited by research in Health Informatics (29 citations), Family Practice (29 citations), Gender Studies (48 citations), Management Science and Operations Research (49 citations) and Public Health, Environmental and Occupational Health (115 citations). Daniel Jurich has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Jason P. Kopp, Tracy E. Zinn, Sara J. Finney, Richard A. Feinberg, Laine Bradshaw, Miguel Paniagua, Christine E. DeMars, Sally A. Santen, Michael Barone and Michelle Daniel. Their work appears in journals such as Academic Medicine, Applied Psychological Measurement, Applied Measurement in Education, Journal of surgical education and International Journal of Testing.

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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