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AIC model selection and multimodel inference in behavioral ecology: some background, observations, and comparisons
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“AIC-based stepwise model selection was performed to select the best-fitting model and to diminish overfitting and favoring a more parsimonious model (Burnham et al., 2011).”
From Perceived restorativeness and environment quality in relation to well-being, residential satisfaction, and sense of community: an analysis in Northeast Italy (2025) · cites this paper as Burnham et al., 2011
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“The selection algorithm can be based on preferable variables and models according to certain statistical criteria (Burnham and Anderson 2002; Burnham et al. 2011).”
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“…structure and an ecological response is evaluated by considering the size of the correlation coefficient, the regression slope or the information value (sensu Burnham et al., 2011) of models in which a measure of landscape structure is the predictor and an ecological measure is the response (Fig.”
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Model selection and model averaging in behavioural ecology: the utility of the IT-AIC framework
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Effects of Humans on Behaviour of Wildlife Exceed Those of Natural Predators in a Landscape of Fear
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A quantitative assessment of fish passage efficiency
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“A model in a set can be considered plausible if its ΔAICc is below 7 (Burnham et al. 2011).”
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“…approach to model selection and variable selection in regression analyses than the more common method of simple significance testing (Akaike, 1974; McQuarrie and Tsai, 1998; Anderson et al., 2000; Johnson and Omland, 2004; Burnham et al., 2011; Garamszegi, 2011; Symonds and Moussalli, 2011).”
MethodDelgado‐Baquerizo, M., Giaramida, L., Reich, P. B., Khachane, A. N., Hamonts, K., Edwards, C., Lawton, L. A., & Singh, B. K. (2016) · Journal of Ecology · doi:10.1111/1365-2745.12585 · Cited by 276
Gilderbloom, J. I. “., Riggs, W. W., & Meares, W. L. (2014) · Cities · doi:10.1016/j.cities.2014.08.001 · Cited by 246
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Lerman, S. B., Contosta, A. R., Milam, J. C., & Bang, C. (2018) · Biological Conservation · doi:10.1016/j.biocon.2018.01.025 · Cited by 244
“For all models that reached convergence, the optimal random effects structure (random intercept and/ or slope) was determined with Akaike's Information Criteria for small sample sizes (AICc; Burnham et al., 2011).”
MethodKahl, T., Arnstadt, T., Baber, K., Bässler, C., Bauhus, J., Borken, W., Buscot, F., Floren, A., Heibl, C., Hessenmöller, D., et al. (2017) · Forest Ecology and Management · doi:10.1016/j.foreco.2017.02.012 · Cited by 232
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“To do so, we used multi-model inference, based on a global model with all candidate variables followed by model selection (Burnham et al. 2011).”
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Spectral properties of 441 radio pulsars
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Practical advice on variable selection and reporting using Akaike information criterion
Sutherland, C. S., Hare, D., Johnson, P. J., Linden, D. W., Montgomery, R. A., & Dröge, E. (2023) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2023.1261 · Cited by 250
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“To determine which of these explanatory variables were the most decisive in possible changes in species richness, community structure, functional diversity and functional trait attributes we used an information theoretical approach based on the Akaike Information Criterion of Second Order (AICc), which is indicated fo…”
MethodHindell, M. A., McMahon, C. R., Bester, M. N., Boehme, L., da Costa, D. P., Fedak, M. A., Guinet, C., Herráiz‐Borreguero, L., Harcourt, R. G., Hückstädt, L. A., et al. (2016) · Ecosphere · doi:10.1002/ecs2.1213 · Cited by 209
“This measure of model parsimony identifies the/those model(s) from a set of candidate models that minimizes K- L information loss (Burnham and Anderson 2004, Burnham et al. 2011) with the relative likelihoods of candidate models calculated using AIC weights.”
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Veilleux, C. C., & Kirk, E. C. (2014) · Brain Behavior and Evolution · doi:10.1159/000357830 · Cited by 204
“When ΔAIC was <2, the models were considered equivalent [Burnham et al., 2011; Symonds and Moussalli, 2011].”
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Magrach, A., González‐Varo, J. P., Boiffier, M., Vilà, M., & Bartomeus, Í. (2017) · Nature Ecology & Evolution · doi:10.1038/s41559-017-0249-9 · Cited by 204
Jankowski, J. E., Merkord, C. L., Farfán-Ríos, W., Cabrera, K. G., Salinas, N., & Silman, M. R. (2012) · Journal of Biogeography · doi:10.1111/jbi.12041 · Cited by 210
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“We considered as plausible all models at ΔAIC b 2 from the best model (Burnham et al., 2011).”
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Richardson, D. C., Holgerson, M. A., Farragher, M. J., Hoffman, K. K., King, K. B. S., Alfonso, M. B., Andersen, M. R., Cheruveil, K. S., Coleman, K. A., Farruggia, M. J., et al. (2022) · Scientific Reports · doi:10.1038/s41598-022-14569-0 · Cited by 188
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“A model matrix was considered to better predict the observed matrix when having a smaller value of AIC, and models with DAIC <14 as equivalents (Burnham et al. 2011).”
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“Moreover, this kind of modeling provides a relative measure of the importance of each predictor among all candidate models [61].”
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“Expanding to consider models with ΔAIC<4, which are still considered to have some support (Burnham et al., 2011), we see very low model probability (wi=0.”
BackgroundMethodInfluentialFrontiers in quantifying wildlife behavioural responses to chemical pollution
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“First, the multi-model approach could provide a quantitative measure of the relative importance of each explanatory variable [55, 59].”
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“We calculated parameter estimates and 95% confidence intervals (CI), usingmodel averaging with all models with ΔAICc b 7 (Burnham et al., 2011).”
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Self-citationMundry, R. (2010) · Behavioral Ecology and Sociobiology · doi:10.1007/s00265-010-1040-y · Cited by 146
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“We selected the ‘best’ model for each weather element 250 based on the lowest AIC, and considered 7 AIC units to be a meaningful difference 251 between models (Burnham et al., 2011).”
MethodSumasgutner, P., Nemeth, E., Tebb, G., Krenn, H. W., & Gamauf, A. (2014) · Frontiers in Zoology · doi:10.1186/1742-9994-11-48 · Cited by 147
“After each step we calculated the AICc (Akaike Information Criterion, corrected for small sample sizes) and defined the model with the lowest value as the final one [101].”
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The Bogert effect, a factor in evolution
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Losses in microbial functional diversity reduce the rate of key soil processes
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Undescribed species have higher extinction risk than known species
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Palaeohistological Evidence for Ancestral High Metabolic Rate in Archosaurs
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Few regulatory metabolites coordinate expression of central metabolic genes in Escherichia coli
Kochanowski, K., Gerosa, L., Brunner, S. F., Christodoulou, D., Nikolaev, Y., & Sauer, U. (2017) · Molecular Systems Biology · doi:10.15252/msb.20167402 · Cited by 130
Gomez, C., Lawson, J. W., Wright, A. J., Buren, A. D., Tollit, D., & Lesage, V. S. (2016) · Canadian Journal of Zoology · doi:10.1139/cjz-2016-0098 · Cited by 132
“Models with a delta AICc less than 7 (Burnham et al. 2011) and those with Ei < 10 are presented.”
MethodSeabird species vary in behavioural response to drone census
Brisson‐Curadeau, É., Bird, D. M., Burke, C. M., Fifield, D. A., Pace, P. W., Sherley, R. B., & Elliott, K. H. (2017) · Scientific Reports · doi:10.1038/s41598-017-18202-3 · Cited by 132
Klaus, K. V., & Matzke, N. J. (2019) · Systematic Biology · doi:10.1093/sysbio/syz034 · Cited by 130
Information criteria for model selection
Zhang, J., Yang, Y., & Ding, J. (2023) · Wiley Interdisciplinary Reviews Computational Statistics · doi:10.1002/wics.1607 · Cited by 166
“More specifically, the viewpoint that the data-generating model has a complicated unknown structure is prevalent in, for example, biological studies (Anderson & Burnham, 2002; Burnham et al., 2011; Johnson & Omland, 2004). The above statement overlooks that the performance of information criteria in practice may also…”
BackgroundConflict Misleads Large Carnivore Management and Conservation: Brown Bears and Wolves in Spain
Fernández‐Gil, A., Naves, J., Ordiz, A., Quevedo, M., Revilla, E., & Delibes, M. (2016) · PLoS ONE · doi:10.1371/journal.pone.0151541 · Cited by 129
“We evaluated model performance and parsimony using Akaike Information Criteria (AIC), the difference (ΔAIC) between each candidate model and the best model (lowest AIC), and AIC weights (AICw [32]).”
MethodRoad avoidance responses determine the impact of heterogeneous road networks at a regional scale
D’Amico, M., Périquet, S., Román, J., & Revilla, E. (2015) · Journal of Applied Ecology · doi:10.1111/1365-2664.12572 · Cited by 127
Huang, S., Waadt, R., Nuhkat, M., Kollist, H., Hedrich, R., & Roelfsema, M. R. G. (2019) · New Phytologist · doi:10.1111/nph.15985 · Cited by 130
Personality-dependent dispersal cancelled under predation risk
Côté, J., Fogarty, S., Tymen, B., Sih, A., & Brodin, T. (2013) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2013.2349 · Cited by 126
P values are only an index to evidence: 20th‐ vs. 21st‐century statistical science
Burnham, K. P., & Anderson, D. R. (2014) · Ecology · doi:10.1890/13-1066.1 · Cited by 124
Self-citationSexually Coercive Male Chimpanzees Sire More Offspring
Feldblum, J. T., Wroblewski, E. E., Rudicell, R. S., Hahn, B. H., Paiva, T., Çetinkaya-Rundel, M., Pusey, A. E., & Gilby, I. C. (2014) · Current Biology · doi:10.1016/j.cub.2014.10.039 · Cited by 131
“we determined the best set of predictors using AIC as the model selection criterion [14, 40] and ranked the resulting models by DAICc, considering those with values % 2 (with respect to the best model) to have substantial support [41].”
Heterogeneity and longevity of antibody memory to viruses and vaccines
Antia, A., Ahmed, H., Handel, A., Carlson, N. E., Amanna, I. J., Antia, R., & Slifka, M. (2018) · PLOS Biology · doi:10.1371/journal.pbio.2006601 · Cited by 123
What drives human–carnivore conflict in the North West Province of South Africa?
Thorn, M., Green, M. W., Dalerum, F., Bateman, P. W., & Scott, D. M. (2012) · Biological Conservation · doi:10.1016/j.biocon.2012.02.017 · Cited by 123
“Models within 7 DAICc units of the model with the lowest AICc (DAICc 6 7) were considered to have sufficient relative support to be included in the final set of explanatory models (Burnham and Anderson, 2002; Burnham et al., 2011).”
MethodExtent and fragmentation of suitable leopard habitat in South Africa
Swanepoel, L., Lindsey, P. A., Somers, M. J., van Hoven, W., & Dalerum, F. (2013) · Animal Conservation · doi:10.1111/j.1469-1795.2012.00566.x · Cited by 130
McClure, M. L., Burdett, C. L., Farnsworth, M. L., Lutman, M. W., Theobald, D. M., Riggs, P. D., Grear, D. A., & Miller, R. S. (2015) · PLoS ONE · doi:10.1371/journal.pone.0133771 · Cited by 122
England, B. J., Brigati, J. R., Schussler, E. E., & Musgrove, M. M. C. (2019) · CBE—Life Sciences Education · doi:10.1187/cbe.17-12-0284 · Cited by 142
Metadata
- Authors
- Burnham, K. P., Anderson, D. R., & Huyvaert, K. P.
- Affiliations
- Colorado State University (US)
- Corresponding author
- Burnham, Kenneth P.
- ORCID
- Huyvaert, Kathryn P.
- Venue
- Behavioral Ecology and Sociobiology
- Published
- 2010-08-18
- Volume
- 65
- Issue
- 1
- Pages
- 23-35
- ISSN
- 0340-5443 (ISSN-L)
- 1432-0762
- OpenAlex
- W2096650374
- Semantic Scholar
- 33e08c84858e01d75d94592e03272dd4073316ff
- Cited by
- 4,104
- References
- 95
- Citations by year
- 2026: 228 · 2025: 300 · 2024: 327 · 2023: 365 · 2022: 358 · 2021: 434 · 2020: 404 · 2019: 335 · 2018: 340 · 2017: 251 · 2016: 239 · 2015: 192 · 2014: 154 · 2013: 98 · 2012: 53
- FWCI
- 44.95
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Behavioral Ecology and Sociobiology (publishedVersion)
- Funders
- Colorado State University
- Innovative Research Group Project of the National Natural Science Foundation of China
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Inference
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Keywords
- AIC model selection, multi-model inference, alternative hypothesis, hypothesis testing, behavioral ecology, statistical inference, probability models
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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