Daniel Fernández
- Applied Psychology top 5%
- Health top 10%
- Health disparities and outcomes 6
- Clinical Psychology top 10%
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- Bayesian Methods and Mixture Models 10
- Advanced Clustering Algorithms Research 4
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- Statistical Methods and Bayesian Inference 9
- Advanced Statistical Methods and Models 6
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- COVID-19 epidemiological studies 6
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- Sensory Analysis and Statistical Methods 5
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- Mental Health Research Topics 4
- Co-authors
- Joan RibasVega González-BuesoElena MonteroJuan José Villalaín SantamaríaLaura MerinoIvy LiuSusana Jiménez‐MúrciaAmparo del Pino‐Gutiérrez
- Journals
- International Journal of Environmental Research and Public Health (3 papers)Frontiers in Psychology (2 papers)Wiley Interdisciplinary Reviews Computational Statistics (2 papers)
- Partner nations
- SpainNew ZealandUnited States
In The Last Decade
Daniel Fernández
49 papers receiving 851 citations
Hit Papers
Peers
Comparison fields: 5 of 126
- Applied Psychology 114
- Health 90
- Sociology and Political Science 408
- Neuropsychology and Physiological Psychology 14
- Clinical Psychology 194
Countries citing papers authored by Daniel Fernández
This map shows the geographic impact of Daniel Fernández'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 Daniel Fernández with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Fernández more than expected).
Fields of papers citing papers by Daniel Fernández
This network shows the impact of papers produced by Daniel Fernández. 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 Daniel Fernández. The network helps show where Daniel Fernández may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Daniel Fernández, 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 | 2024 | 0 | |
| 2 | 2023 | 0 | |
| 3 | 2023 | 2 | |
| 4 | 2023 | 7 | |
| 5 | 2022 | 29 | |
| 6 | 2022 | 2 | |
| 7 | 2022 | 2 | |
| 8 | 2021 | 2 | |
| 9 | 2021 | 21 | |
| 10 | 2021 | 2 | |
| 11 | 2021 | 20 | |
| 12 | 2021 | 1 | |
| 13 | 2021 | 9 | |
| 14 | 2020 | 33 | |
| 15 | 2020 | 16 | |
| 16 | 2020 | 29 | |
| 17 | 2020 | 3 | |
| 18 | 2020 | 32 | |
| 19 | 2018 | 4 | |
| 20 | 2016 | 7 |
About Daniel Fernández
Daniel Fernández is a scholar working on Statistics and Probability, Modeling and Simulation and Health, having authored 55 papers that have together received 871 indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (10 papers), Statistical Methods and Bayesian Inference (9 papers), COVID-19 epidemiological studies (6 papers), Advanced Statistical Methods and Models (6 papers), Health disparities and outcomes (6 papers), Sensory Analysis and Statistical Methods (5 papers), Advanced Clustering Algorithms Research (4 papers) and Mental Health Research Topics (4 papers). The work is most often cited by research in Applied Psychology (114 citations), Health (90 citations) and Sociology and Political Science (408 citations). Daniel Fernández has collaborated with scholars based in Spain, New Zealand and United States. Frequent co-authors include Joan Ribas, Vega González-Bueso, Elena Montero, Juan José Villalaín Santamaría, Laura Merino, Ivy Liu, Susana Jiménez‐Múrcia, Amparo del Pino‐Gutiérrez, Richard Arnold and Shirley Pledger. Their work appears in journals such as International Journal of Environmental Research and Public Health, Frontiers in Psychology, Wiley Interdisciplinary Reviews Computational Statistics, BMJ Open and Statistics in Medicine.
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.