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 diminish overfitting.
“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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“A model in a set can be considered plausible if its ΔAICc is below 7 (Burnham et al. 2011).”
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Curran, M. P., Hellweg, S., & Beck, J. (2013) · Ecological Applications · doi:10.1890/13-0243.1 · Cited by 295 · see citing works
Microbial richness and composition independently drive soil multifunctionality
Delgado‐Baquerizo, M., Trivedi, P., Trivedi, C., Eldridge, D. J., Reich, P. B., Jeffries, T. C., & Singh, B. K. (2017) · Functional Ecology · doi:10.1111/1365-2435.12924 · Cited by 289 · see citing works
Human selection of elk behavioural traits in a landscape of fear
Ciuti, S., Muhly, T. B., Paton, D. G., McDevitt, A. D., Musiani, M., & Boyce, M. S. (2012) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2012.1483 · Cited by 277 · see citing works
Too hot to handle: Unprecedented seagrass death driven by marine heatwave in a World Heritage Area
Strydom, S., Murray, K. L., Wilson, S. K., Huntley, B., Rule, M. J., Heithaus, M. R., Bessey, C., Kendrick, G. A., Burkholder, D. A., Fraser, M. W., et al. (2020) · Global Change Biology · doi:10.1111/gcb.15065 · Cited by 273 · see citing works
Gender Gaps in Achievement and Participation in Multiple Introductory Biology Classrooms
Eddy, S. L., Brownell, S. E., & Wenderoth, M. P. (2014) · CBE—Life Sciences Education · doi:10.1187/cbe.13-10-0204 · Cited by 281 · see citing works
“…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 268 · see citing works
Gilderbloom, J. I. “., Riggs, W. W., & Meares, W. L. (2014) · Cities · doi:10.1016/j.cities.2014.08.001 · Cited by 246 · see citing works
To mow or to mow less: Lawn mowing frequency affects bee abundance and diversity in suburban yards
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 · see citing works
“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 · see citing works
Solar, R., Barlow, J., Andersen, A. N., Schoereder, J. H., Berenguer, É., Ferreira, J., & Gardner, T. A. (2016) · Biological Conservation · doi:10.1016/j.biocon.2016.03.005 · Cited by 231 · see citing works
“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).”
MethodUsing the BirdTree.org website to obtain robust phylogenies for avian comparative studies: A primer
Rubolini, D., Liker, A., Garamszegi, L. Z., Møller, A. P., & Saino, N. (2015) · Current Zoology · doi:10.1093/czoolo/61.6.959 · Cited by 227 · see citing works
Spectral properties of 441 radio pulsars
Jankowski, F., van Straten, W., Keane, E. F., Bailes, M., Barr, E. D., Johnston, S., & Kerr, M. T. (2017) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/stx2476 · Cited by 221 · see citing works
Practical advice on variable selection and reporting using Akaike information criterion
Sutherland, C., Hare, D., Johnson, P. J., Linden, D., Montgomery, R., & Droge, E. (2023) · Proceedings of the Royal Society B · doi:10.1098/rspb.2023.1261 · Cited by 232 · see citing works
Fisher, J. C., Irvine, K. N., Bicknell, J. E., Hayes, W. M., Fernandes, D., Mistry, J., & Davies, Z. G. (2020) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2020.143095 · Cited by 220 · see citing works
McCune, J. L. (2016) · Journal of Applied Ecology · doi:10.1111/1365-2664.12702 · Cited by 212 · see citing works
Magnago, L. F. S., Edwards, D. P., Edwards, F. A., Magrach, A., Martins, S. V., & Laurance, W. F. (2013) · Journal of Ecology · doi:10.1111/1365-2745.12206 · Cited by 209 · see citing works
“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 · see citing works
“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.”
MethodInfluentialVisual Acuity in Mammals: Effects of Eye Size and Ecology
Veilleux, C. C., & Kirk, E. C. (2014) · Brain Behavior and Evolution · doi:10.1159/000357830 · Cited by 204 · see citing works
“When ΔAIC was <2, the models were considered equivalent [Burnham et al., 2011; Symonds and Moussalli, 2011].”
MethodHoneybee spillover reshuffles pollinator diets and affects plant reproductive success
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 203 · see citing works
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 205 · see citing works
Cope's rule and the adaptive landscape of dinosaur body size evolution
Benson, R., Hunt, G., Carrano, M. T., & Campione, N. E. (2017) · Palaeontology · doi:10.1111/pala.12329 · Cited by 203 · see citing works
Testing Similarity Effects with Dyadic Response Surface Analysis
Schönbrodt, F. D., Humberg, S., & Nestler, S. (2018) · European Journal of Personality · doi:10.1002/per.2169 · Cited by 202 · see citing works
Kalan, A. K., Mundry, R., Wagner, O. J. J., Heinicke, S., Boesch, C., & Kühl, H. S. (2015) · Ecological Indicators · doi:10.1016/j.ecolind.2015.02.023 · Cited by 200 · see citing works
Emotions in goats: mapping physiological, behavioural and vocal profiles
Briefer, E. F., Tettamanti, F., & McElligott, A. G. (2014) · Animal Behaviour · doi:10.1016/j.anbehav.2014.11.002 · Cited by 197 · see citing works
Landscape‐level crop diversity benefits biological pest control
Redlich, S., Martin, E. A., & Steffan-Dewenter, I. D. (2018) · Journal of Applied Ecology · doi:10.1111/1365-2664.13126 · Cited by 190 · see citing works
Leroux, S. (2019) · PLoS ONE · doi:10.1371/journal.pone.0206711 · Cited by 192 · see citing works
A New Criterion for Model Selection
Pham, H. (2019) · Mathematics · doi:10.3390/math7121215 · Cited by 190 · see citing works
Vertebrate road-kill patterns in Mediterranean habitats: Who, when and where
D’Amico, M., Román, J., Reyes, L. D. L., & Revilla, E. (2015) · Biological Conservation · doi:10.1016/j.biocon.2015.06.010 · Cited by 189 · see citing works
“We considered as plausible all models at ΔAIC b 2 from the best model (Burnham et al., 2011).”
MethodA functional definition to distinguish ponds from lakes and wetlands
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 · see citing works
Galipaud, M., Gillingham, M. A. F., David, M., & Dechaume‐Moncharmont, F. (2014) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.12251 · Cited by 181 · see citing works
Secondary forest fragments offer important carbon and biodiversity cobenefits
Matos, F. A. R., Magnago, L. F. S., Miranda, C. A. C., de Menezes, L. F. T., Gastauer, M., Safar, N. V. H., Schaefer, C. E. G. R., Silva, M. P. D., Simonelli, M., Edwards, F. A., et al. (2019) · Global Change Biology · doi:10.1111/gcb.14824 · Cited by 178 · see citing works
The importance of scattered trees for biodiversity conservation: A global meta‐analysis
Prevedello, J. A., Almeida‐Gomes, M., & Lindenmayer, D. B. (2017) · Journal of Applied Ecology · doi:10.1111/1365-2664.12943 · Cited by 179 · see citing works
Wei, D., Zhuang, K., Ai, L., Chen, Q., Yang, W., Liu, W., Wang, K., Sun, J., & Qiu, J. (2018) · Scientific Data · doi:10.1038/sdata.2018.134 · Cited by 178 · see citing works
Brownscombe, J. W., Lédée, E. J. I., Raby, G. D., Struthers, D. P., Gutowsky, L. F. G., Nguyen, V. M., Young, N., Stokesbury, M. J. W., Holbrook, C. M., Brenden, T. O., et al. (2019) · Reviews in Fish Biology and Fisheries · doi:10.1007/s11160-019-09560-4 · Cited by 176 · see citing works
Morphological and Spatio‐Temporal Mismatches Shape a Neotropical Savanna Plant‐Hummingbird Network
Maruyama, P. K., Vizentin‐Bugoni, J., de Oliveira, G. M., Oliveira, P. E., & Dalsgaard, B. (2014) · Biotropica · doi:10.1111/btp.12170 · Cited by 176 · see citing works
“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).”
MethodUsing information theory as a substitute for stepwise regression in ecology and behavior
Hegyi, G., & Garamszegi, L. Z. (2010) · Behavioral Ecology and Sociobiology · doi:10.1007/s00265-010-1036-7 · Cited by 171 · see citing works
Landslide Susceptibility Mapping: Machine and Ensemble Learning Based on Remote Sensing Big Data
Kalantar, B., Ueda, N., Saeidi, V., Ahmadi, K., Halin, A. B. A., & Shabani, F. (2020) · Remote Sensing · doi:10.3390/rs12111737 · Cited by 169 · see citing works
“Moreover, this kind of modeling provides a relative measure of the importance of each predictor among all candidate models [61].”
BackgroundZhang, L., & Xu, J. (2025) · The Internet and Higher Education · doi:10.1016/j.iheduc.2024.100978 · Cited by 168 · see citing works
Virological factors that increase the transmissibility of emerging human viruses
Geoghegan, J. L., Senior, A. M., Di Giallonardo, F., & Holmes, E. C. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1521582113 · Cited by 155 · see citing works
Mezei, P., Jakuš, R., Pennerstorfer, J., Potterf, M., Škvarenina, J., Ferenčík, J., Slivinský, J., Bíčárová, S., Bilčík, D., Blaženec, M., et al. (2017) · Agricultural and Forest Meteorology · doi:10.1016/j.agrformet.2017.04.004 · Cited by 167 · see citing works
Geographical variation in mutualistic networks: similarity, turnover and partner fidelity
Trøjelsgaard, K., Jordano, P., Carstensen, D., & Olesen, J. M. (2015) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2014.2925 · Cited by 163 · see citing works
Tree mode of death and mortality risk factors across Amazon forests
Esquivel‐Muelbert, A., Phillips, O. L., Brienen, R., Fauset, S., Sullivan, M. J. P., Baker, T. R., Chao, K., Feldpausch, T. R., Gloor, E. U., Higuchi, N., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-18996-3 · Cited by 163 · see citing works
Sun, J., Ma, B., & Lu, X. (2017) · Land Degradation and Development · doi:10.1002/ldr.2822 · Cited by 162 · see citing works
Visual acuity in ray-finned fishes correlates with eye size and habitat
Caves, E. M., Sutton, T., & Johnsen, S. (2017) · Journal of Experimental Biology · doi:10.1242/jeb.151183 · Cited by 160 · see citing works
“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
Bertram, M. G., Martin, J. M., McCallum, E. S., Alton, L. A., Brand, J. A., Brooks, B. W., Červený, D., Fick, J. B., Ford, A. T., Hellström, G., et al. (2022) · Biological reviews/Biological reviews of the Cambridge Philosophical Society · doi:10.1111/brv.12844 · Cited by 162 · see citing works
Drivers of taxonomic bias in conservation research: a global analysis of terrestrial mammals
dos Santos, J. W., Correia, R. A., Malhado, A. C. M., Campos‐Silva, J. V., TELES, D. O., Jepson, P. R., & Ladle, R. J. (2020) · Animal Conservation · doi:10.1111/acv.12586 · Cited by 149 · see citing works
Hu, A., Wang, J., Sun, H., Niu, B., Si, G., Wang, J., Yeh, C.-F., Zhu, X., Lu, X., Zhou, J. Z., et al. (2020) · The ISME Journal · doi:10.1038/s41396-019-0574-x · Cited by 149 · see citing works
“First, the multi-model approach could provide a quantitative measure of the relative importance of each explanatory variable [55, 59].”
MethodEvolutionary Change in Continuous Reaction Norms
Murren, C. J., MacLean, H. J., Diamond, S. E., Steiner, U. K., Heskel, M., Handelsman, C. A., Ghalambor, C. K., Auld, J. R., Callahan, H. S., Pfennig, D. W., et al. (2014) · The American Naturalist · doi:10.1086/675302 · Cited by 147 · see citing works
Improving invasive ant eradication as a conservation tool: A review
Hoffmann, B. D., Luque, G. M., Bellard, C., Holmes, N. D., & Donlan, C. J. (2016) · Biological Conservation · doi:10.1016/j.biocon.2016.03.036 · Cited by 147 · see citing works
“We calculated parameter estimates and 95% confidence intervals (CI), usingmodel averaging with all models with ΔAICc b 7 (Burnham et al., 2011).”
Filippi, P., Congdon, J. V., Hoang, J. G., Bowling, D. L., Reber, S. A., Pašukonis, A., Hoeschele, M., Ocklenburg, S., de Boer, B., Sturdy, C. B., et al. (2017) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2017.0990 · Cited by 142 · see citing works
Predictors of Juvenile Survival in Birds
Maness, T. J., & Anderson, D. J. (2013) · Ornithological Monographs · doi:10.1525/om.2013.78.1.1 · Cited by 144 · see citing works
Self-citationMundry, R. (2010) · Behavioral Ecology and Sociobiology · doi:10.1007/s00265-010-1040-y · Cited by 143 · see citing works
Hill, D. L., & Wall, E. (2015) · Animal · doi:10.1017/s1751731114002456 · Cited by 143 · see citing works
“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 141 · see citing works
“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].”
MethodDainese, M., Montecchiari, S., Sitzia, T., Sigura, M., & Marini, L. (2016) · Journal of Applied Ecology · doi:10.1111/1365-2664.12747 · Cited by 142 · see citing works
The Bogert effect, a factor in evolution
Muñoz, M. M. (2021) · Evolution · doi:10.1111/evo.14388 · Cited by 139 · see citing works
Losses in microbial functional diversity reduce the rate of key soil processes
Trivedi, C., Delgado‐Baquerizo, M., Hamonts, K., Lai, K., Reich, P. B., & Singh, B. K. (2019) · Soil Biology and Biochemistry · doi:10.1016/j.soilbio.2019.05.008 · Cited by 135 · see citing works
Undescribed species have higher extinction risk than known species
Liu, J., Slik, F. J. W., Zheng, S., & Lindenmayer, D. B. (2022) · Conservation Letters · doi:10.1111/conl.12876 · Cited by 141 · see citing works
Palaeohistological Evidence for Ancestral High Metabolic Rate in Archosaurs
Legendre, L. J., Guénard, G., Botha, J., & Cubo, J. (2016) · Systematic Biology · doi:10.1093/sysbio/syw033 · Cited by 135 · see citing works
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 128 · see citing works
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 · see citing works
“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 · see citing works
Klaus, K. V., & Matzke, N. J. (2019) · Systematic Biology · doi:10.1093/sysbio/syz034 · Cited by 126 · see citing works
Information criteria for model selection
Zhang, J., Yang, Y., & Ding, J. (2023) · Wiley Interdisciplinary Reviews Computational Statistics · doi:10.1002/wics.1607 · Cited by 131 · see citing works
“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 · see citing works
“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 · see citing works
Huang, S., Waadt, R., Nuhkat, M., Kollist, H., Hedrich, R., & Roelfsema, M. R. G. (2019) · New Phytologist · doi:10.1111/nph.15985 · Cited by 127 · see citing works
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 · see citing works
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 · see citing works
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 124 · see citing works
“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 · see citing works
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 · see citing works
“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 · see citing works
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 · see citing works
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 · see citing works
- 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
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