Janet Mee

25 papers receiving 333 citations

Peers

Janet Mee
Comparison fields: 5 of 65
  • Family Practice 66
  • Health Informatics 10
  • Public Health, Environmental and Occupational Health 129
  • Management Science and Operations Research 40
  • Statistics, Probability and Uncertainty 17
Replace Polina Harik with:
Polina Harik United States
André De Champlain Canada
Kathleen Z. Holtzman United States
D R Ripkey United States
Gwendolyn C. Murphy United States
M Corn United States
Justine Pang United States
Badisse Dahamna France
Christopher Harrison United Kingdom
Curtis L. Cole United States
Janet Mee relative to Polina Harik United States Polina Harik's profile →
Citations per field
00.5×1.5×
Polina Harik · 1×
Citations per year

Countries citing papers authored by Janet Mee

Since Specialization
Citations

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

Fields of papers citing papers by Janet Mee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200656
2 201153
3 200939
4 201931
5 201928
6 201114
7 200913
8 201612
9 202012
10 200911
11 201211
12 200811
13
Predicting Item Survival for Multiple Choice Questions in a High-Stakes Medical Exam.
20209
14 20138
15 20046
16 20176
17 20235
18 20195
19 20234
20 20213

About Janet Mee

Janet Mee is a scholar working on Artificial Intelligence, Public Health, Environmental and Occupational Health, Management Science and Operations Research, Statistics, Probability and Uncertainty and Family Practice, having authored 25 papers that have together received 346 indexed citations. Recurring topics across this work include Topic Modeling (5 papers), Psychometric Methodologies and Testing (4 papers), Reliability and Agreement in Measurement (4 papers), Innovations in Medical Education (4 papers), Natural Language Processing Techniques (3 papers), Clinical Reasoning and Diagnostic Skills (3 papers), Radiology practices and education (2 papers) and Meta-analysis and systematic reviews (2 papers). The work is most often cited by research in Family Practice (66 citations), Health Informatics (10 citations), Public Health, Environmental and Occupational Health (129 citations), Management Science and Operations Research (40 citations) and Statistics, Probability and Uncertainty (17 citations). Janet Mee has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Brian E. Clauser, Melissa J. Margolis, Polina Harik, Victoria Yaneva, Le An Ha, Mark R. Raymond, Steven A. Haist, Ann King, Richard E. Hawkins and Gerard F. Dillon. Their work appears in journals such as Academic Medicine, Journal of Educational Measurement, Educational Measurement Issues and Practice, Evaluation & the Health Professions and Journal of Biomedical Informatics.

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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