Carsten F. Dormann: h-index, Total Citations, and Citation Map
Carsten F. Dormann's h-index is 89 (173 i10-index, 60,030+ total citations across 4+ publications) according to Google Scholar as of May 2026. Carsten F. Dormann is affiliated with Professor for Biometry and Environmental System Analysis, University of Freiburg.
Carsten F. Dormann is a researcher affiliated with Professor for Biometry and Environmental System Analysis, University of Freiburg, specializing in statistical ecology. Their work has been cited 60,030 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Carsten F. Dormann's Citation Metrics
Bibliometric impact based on 4 indexed publications. Of these, 2 are original research articles — the rest are literature highlights, conference abstracts or theses.
- H-Index
- 89
- i10-Index
- 173
- Total Citations
- 60,030
- Citing Countries
- 32
As of May 2026.
Carsten F. Dormann has an h-index of 89 and 60,030 total citations across 4 publications, with research cited by institutions in 32 countries.
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Top Cited Works
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Collinearity: a review of methods to deal with it and a simulation study evaluating their performance
201312,134
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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 provided a seminal review and simulation study evaluating methods to address collinearity, establishing a highly cited benchmark for statistical methodology.
The researcher provided a seminal review of methods for accounting for spatial autocorrelation in species distributional data, establishing a critical methodological framework for ecological analysis.
The researcher developed rigorous cross-validation strategies for complex data structures, establishing a foundational methodological standard widely adopted across scientific disciplines.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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