F. Jay Breyer

414 citations
10 papers · 272 · h-index 5

Impact in

Papers in

F. Jay Breyer

10 papers receiving 252 citations

Peers

F. Jay Breyer
Comparison fields: 5 of 51
  • Computer Science Applications 32
  • Developmental and Educational Psychology 59
  • Statistics, Probability and Uncertainty 33
  • Health Informatics 6
  • Artificial Intelligence 134
Replace Masaki Uto with:
Masaki Uto Japan
Chi Lu United States
Jinnie Shin United States
Ahmed Maalel Tunisia
Jennifer J. Kaplan United States
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Citations per year

Countries citing papers authored by F. Jay Breyer

Since Specialization
Citations

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

Fields of papers citing papers by F. Jay Breyer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by F. Jay Breyer. 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 F. Jay Breyer. The network helps show where F. Jay Breyer may publish in the future.

Co-authors

The 14 scholars most cited alongside F. Jay Breyer, 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 F. Jay Breyer Line = papers co-authored together F. Jay Breyer links everyone, so they are left out of the graph.

All Works

10 of 10 papers shown
#Work
1 2012234
2 20148
3 19947
4 20176
5 20126
6
A Study of the Use of the "e-rater"® Scoring Engine for the Analytical Writing Measure of the "GRE"® revised General Test. Research Report. ETS RR-14-24.
20143
7 20133
8
Implementing a Contributory Scoring Approach for the "GRE"® Analytical Writing Section: A Comprehensive Empirical Investigation. Research Report. ETS RR-17-14.
20172
9 20152
10 19941

About F. Jay Breyer

F. Jay Breyer is a scholar working on Management Science and Operations Research, Statistics, Probability and Uncertainty, Information Systems, Artificial Intelligence and Surgery, having authored 10 papers that have together received 272 indexed citations. Recurring topics across this work include Psychometric Methodologies and Testing (6 papers), Reliability and Agreement in Measurement (4 papers), Software Engineering Research (2 papers), Advanced Text Analysis Techniques (1 paper), Healthcare Systems and Technology (1 paper), Health Sciences Research and Education (1 paper), Advanced Statistical Process Monitoring (1 paper) and Intelligent Tutoring Systems and Adaptive Learning (1 paper). The work is most often cited by research in Computer Science Applications (32 citations), Developmental and Educational Psychology (59 citations), Statistics, Probability and Uncertainty (33 citations), Health Informatics (6 citations) and Artificial Intelligence (134 citations). F. Jay Breyer has collaborated with scholars based in United States. Frequent co-authors include David M. Williamson, Xiaoming Xi, Charles Lewis, Brent Bridgeman, Catherine Trapani, Yigal Attali, Mo Zhang, Chaitanya Ramineni, André A. Rupp and André Rupp. Their work appears in journals such as International Journal of Testing, Educational Measurement Issues and Practice, ETS Research Report Series and Laboratory Medicine.

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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