Jim Albert: h-index, Total Citations, and Citation Map
Jim Albert's h-index is 37 (80 i10-index, 11,537+ total citations across 5+ publications) according to Google Scholar as of May 2026. Jim Albert is affiliated with Emeritus Professor of Statistics, Bowling Green State University.
Jim Albert is a researcher affiliated with Emeritus Professor of Statistics, Bowling Green State University, specializing in Statistics, Bayesian Statistics, Statistics in Sports. Their work has been cited 11,537 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Jim Albert's Citation Metrics
Bibliometric impact based on 5 indexed publications.
- H-Index
- 37
- i10-Index
- 80
- Total Citations
- 11,537
- Citing Countries
- 12
As of May 2026.
Jim Albert has an h-index of 37 and 11,537 total citations across 5 publications, with research cited by institutions in 12 countries.
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Global Impact Map
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Top Cited Works
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Bayesian analysis of binary and polychotomous response data
19934,686
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Top Citing Institutions
Visa Evidence Package
Views and exports tuned for EB-1A, O-1A, and EB-2 NIW petitions. Sustained acclaim, geographic reach, and independent-citation filtering are the strongest evidence categories immigration adjudicators look for.
Significant Contributions
Auto-detected research lines — a seminal paper and the follow-up work building on it. Review and edit before using in a petition. Each Free PDF opens in a new tab — EB-1A organises this into the structure USCIS applies to Criterion 5 of 8 CFR § 204.5(h)(3)(v); EB-1B re-frames it under § 204.5(i)(3) (outstanding researcher); NIW presents it under prong 2 of Matter of Dhanasar.
The researcher established a foundational Bayesian framework for analyzing binary and polychotomous response data, a seminal contribution that has been widely adopted across diverse scientific disciplines.
The researcher pioneered the application of Gibbs sampling for Bayesian estimation of normal ogive item response curves, establishing a foundational computational method in psychometrics.
The researcher established a foundational framework for ordinal data modeling, as evidenced by the highly cited 2000 monograph that continues to serve as a key reference in the field.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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