James Arbuckle
Impact in
- Clinical Psychology top 5%
- Child and Adolescent Psychosocial and Emotional Development
- Child Abuse and Trauma
- Statistics and Probability top 2%
- Statistical Methods and Bayesian Inference
Papers in
-
- Neural Networks and Applications 2
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- Advanced Statistical Methods and Models 2
- Statistical Methods and Bayesian Inference 1
- Advanced Causal Inference Techniques 1
- Co-authors
- James Larimer (1 shared paper)Michael Friendly (2 shared papers)Leona S. Aiken (1 shared paper)
- Journals
- Behavior Research Methods (3 papers)Psychometrika (2 papers)British Journal of Mathematical and Statistical Psychology (1 paper)Journal of Mathematical Psychology (1 paper)The American Statistician (1 paper)
- Partner nations
- United StatesCanada
In The Last Decade
James Arbuckle
10 papers receiving 1.6k citations
James Arbuckle's Hit Papers
Peers
Comparison fields: 5 of 143
- Clinical Psychology 496
- Statistics and Probability 143
- Social Psychology 346
- Health 127
- Experimental and Cognitive Psychology 201
Countries citing papers authored by James Arbuckle
This map shows the geographic impact of James Arbuckle'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 James Arbuckle with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James Arbuckle more than expected).
Fields of papers citing papers by James Arbuckle
This network shows the impact of papers produced by James Arbuckle. 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 James Arbuckle. The network helps show where James Arbuckle may publish in the future.
Co-authors
The 3 scholars most cited alongside James Arbuckle, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Full Information Estimation in the Presence of Incomplete Data Hit paper breakdown → | 1996 | 1434 |
| 2 | 1989 | 101 | |
| 3 | 1994 | 89 | |
| 4 | EBOOK : IBM SPSS Amos 25 User’s Guide | 2017 | 34 |
| 5 | 1973 | 19 | |
| 6 | 1976 | 12 | |
| 7 | 1977 | 6 | |
| 8 | 1975 | 2 | |
| 9 | 1975 | 1 | |
| 10 | 1979 | 1 | |
| 11 | A collection of letters and essays on several subjects | 2002 | 0 |
| 12 | 1970 | 0 |
About James Arbuckle
James Arbuckle is a scholar working on Artificial Intelligence, Statistics and Probability, Signal Processing, Management Science and Operations Research and Computer Networks and Communications, having authored 12 papers that have together received 1.7k indexed citations. Recurring topics across this work include Blind Source Separation Techniques (2 papers), Multi-Criteria Decision Making (2 papers), Neural Networks and Applications (2 papers), Advanced Statistical Methods and Models (2 papers), Distributed Sensor Networks and Detection Algorithms (1 paper), Reliability and Agreement in Measurement (1 paper), Statistical Methods and Bayesian Inference (1 paper) and Advanced Causal Inference Techniques (1 paper). The work is most often cited by research in Clinical Psychology (496 citations), Statistics and Probability (143 citations), Social Psychology (346 citations), Health (127 citations) and Experimental and Cognitive Psychology (201 citations). James Arbuckle has collaborated with scholars based in United States and Canada. Frequent co-authors include James Larimer, Michael Friendly and Leona S. Aiken. Their work appears in journals such as Behavior Research Methods, Psychometrika, British Journal of Mathematical and Statistical Psychology, Journal of Mathematical Psychology and The American Statistician.
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.