László Zsolt Garamszegi
Biographic Data
| ID | 1809823 |
|---|---|
| NAME | László Zsolt Garamszegi |
| GIVEN NAMES | László Zsolt |
| FAMILY NAME | Garamszegi |
| SIGNATURE | GARAMSZEGI L Z |
| AFFILIATIONS | Estación Biológica de Doñana |
| ORCID | 0000-0001-8920-2183 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 6 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2016 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 1 |
Environmental and socio‐economic factors behind data provision in 17 citizen science projects
Citizen science approaches in ecology have recently become increasingly popular. Although many advantages, such as the cost‐effective collection of vast amounts of data, outweigh the disadvantages, most projects face difficulties, such as non‐random sampling, pseudo‐absences or various biases, such as detection/reporting biases or participant‐related biases. To unravel some of the environmental and socio‐economic factors underlying data provision…
Robustness of linear mixed‐effects models to violations of distributional assumptions
Linear mixed‐effects models are powerful tools for analysing complex datasets with repeated or clustered observations, a common data structure in ecology and evolution. Mixed‐effects models involve complex fitting procedures and make several assumptions, in particular about the distribution of residual and random effects. Violations of these assumptions are common in real datasets, yet it is not always clear how much these violations matter to ac…
Assessing sources of error in comparative analyses of primate behavior
Assessing sources of error in comparative analyses of primate behavior
Robustness of linear mixed‐effects models to violations of distributional assumptions
Linear mixed‐effects models are powerful tools for analysing complex datasets with repeated or clustered observations, a common data structure in ecology and evolution. Mixed‐effects models involve complex fitting procedures and make several assumptions, in particular about the distribution of residual and random effects. Violations of these assumptions are common in real datasets, yet it is not always clear how much these violations matter to ac…
Environmental and socio‐economic factors behind data provision in 17 citizen science projects
Citizen science approaches in ecology have recently become increasingly popular. Although many advantages, such as the cost‐effective collection of vast amounts of data, outweigh the disadvantages, most projects face difficulties, such as non‐random sampling, pseudo‐absences or various biases, such as detection/reporting biases or participant‐related biases. To unravel some of the environmental and socio‐economic factors underlying data provision…
Species Distribution and Climate Change (2 works) · Algorithm (1 work) · Amphibian and Reptile Biology (1 work) · Artificial Intelligence (1 work) · Best linear unbiased prediction (1 work) · Biology (1 work) · Brain size (1 work) · Citizen science (1 work) · Computer Science (1 work) · Context (archaeology) (1 work)