Brian Habing

841 citations
24 papers · 612 · h-index 13

Impact in

Papers in

Brian Habing

24 papers receiving 582 citations

Peers

Brian Habing
Comparison fields: 5 of 94
  • Management Science and Operations Research 234
  • Statistics and Probability 138
  • Applied Psychology 37
  • Computer Networks and Communications 158
  • Experimental and Cognitive Psychology 60
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Citations per field
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Citations per year

Countries citing papers authored by Brian Habing

Since Specialization
Citations

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

Fields of papers citing papers by Brian Habing

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1996132
2 200986
3 201162
4 201849
5 200349
6 199845
7 200726
8 200723
9 201320
10 200519
11 200118
12 201016
13 200514
14 200812
15 200312
16 19967
17
Maximum likelihood estimation with binary-data regression models: small-sample and large-sample features.
20106
18 19984
19 20033
20 20153

About Brian Habing

Brian Habing is a scholar working on Management Science and Operations Research, Computer Networks and Communications, Statistics and Probability, Epidemiology and Applied Psychology, having authored 24 papers that have together received 612 indexed citations. Recurring topics across this work include Psychometric Methodologies and Testing (10 papers), Advanced Statistical Modeling Techniques (9 papers), Statistical Methods and Bayesian Inference (5 papers), Substance Abuse Treatment and Outcomes (3 papers), Advanced Statistical Methods and Models (3 papers), Multi-Criteria Decision Making (2 papers), Optimism, Hope, and Well-being (2 papers) and Statistical Methods and Inference (2 papers). The work is most often cited by research in Management Science and Operations Research (234 citations), Statistics and Probability (138 citations), Applied Psychology (37 citations), Computer Networks and Communications (158 citations) and Experimental and Cognitive Psychology (60 citations). Brian Habing has collaborated with scholars based in United States and South Korea. Frequent co-authors include John S. Cacciola, Arthur I. Alterman, Jeff Douglas, Louis A. Roussos, Kevin G. Lynch, Holmes Finch, William Stout, Jinming Zhang, Megan Ivey and A. Thomas McLellan. Their work appears in journals such as Applied Psychological Measurement, Journal of Educational and Behavioral Statistics, Addiction, Structural Equation Modeling A Multidisciplinary Journal and Journal of Educational Measurement.

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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