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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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Factors Associated With 8-Year Mortality in Older Patients With Cerebral Small Vessel Disease
van der Holst, H. M., van Uden, I. W. M., Tuladhar, A. M., de Laat, K. F., van Norden, A. G. W., Norris, D. G., van Dijk, E. J., Rutten‐Jacobs, L. C. A., & de Leeuw, F. (2016) · JAMA Neurology · doi:10.1001/jamaneurol.2015.4560 · Cited by 64
Yang, T., Zhao, Y., & Song, Q. (2016) · Social Science Research · doi:10.1016/j.ssresearch.2016.06.011 · Cited by 63
Grizzly bears without borders: Spatially explicit capture–recapture in southwestern Alberta
Morehouse, A. T., & Boyce, M. S. (2016) · Journal of Wildlife Management · doi:10.1002/jwmg.21104 · Cited by 60
Meillère, A., Brischoux, F., Henry, P., Michaud, B., Garcin, R., & Angelier, F. (2017) · Landscape and Urban Planning · doi:10.1016/j.landurbplan.2016.12.014 · Cited by 63
Gilby, B. L., Olds, A. D., Connolly, R. M., Yabsley, N. A., Maxwell, P., Tibbetts, I. R., Schoeman, D. S., & Schlacher, T. A. (2017) · Estuarine Coastal and Shelf Science · doi:10.1016/j.ecss.2017.10.003 · Cited by 63
“Best fit models were those with the lowest AICc value, and those within two DAICc units (Burnham et al., 2011).”
MethodThe UTMOST pulsar timing programme I: Overview and first results
Jankowski, F., Bailes, M., van Straten, W., Keane, E. F., Flynn, C., Barr, E. D., Bateman, T., Bhandari, S., Caleb, M., Campbell‐Wilson, D., et al. (2018) · Monthly Notices of the Royal Astronomical Society · doi:10.1093/mnras/sty3390 · Cited by 63
Island biogeography of mutualistic interaction networks
Trøjelsgaard, K., Báez, M., Espadaler, X., Nogales, M., Oromı́, P., Roche, F. L., & Olesen, J. M. (2013) · Journal of Biogeography · doi:10.1111/jbi.12165 · Cited by 62
“We applied an information-theoretical approach based on the Akaike information criterion (AIC) to evaluate our models (Burnham et al., 2011).”
BackgroundMethodInfluentialWirsing, A. J., Quinn, T. P., Cunningham, C. J., Adams, J. R., Craig, A. D., & Waits, L. P. (2018) · Ecology and Evolution · doi:10.1002/ece3.4431 · Cited by 62
The limits of demographic buffering in coping with environmental variation
Rodríguez‐Caro, R. C., Capdevila, P., Graciá, E., Barbosa, J. M., Giménez, A., & Salguero‐Gómez, R. (2021) · Oikos · doi:10.1111/oik.08343 · Cited by 63
Htay, T., Htoo, K. K., Mbise, F. P., & Røskaft, E. (2022) · Society & Natural Resources · doi:10.1080/08941920.2022.2032515 · Cited by 62
Nardi, D., Jactel, H., Pagot, E., Samalens, J.-C., & Marini, L. (2022) · Agricultural and Forest Entomology · doi:10.1111/afe.12536 · Cited by 62
Feral wild boar distribution and perceptions of risk on the central Canadian prairies
Brook, R. K., & van Beest, F. M. (2014) · Wildlife Society Bulletin · doi:10.1002/wsb.424 · Cited by 62
“Model selection was conducted using a multi-model inference technique based on model-averaging (Burnham et al. 2011).”
BackgroundMethodCan multitrophic interactions and ocean warming influence large‐scale kelp recovery?
Christie, H., Gundersen, H., Rinde, E., Filbee‐Dexter, K., Norderhaug, K. M., Pedersen, T., Bekkby, T., Gitmark, J. K., & Fagerli, C. W. (2019) · Ecology and Evolution · doi:10.1002/ece3.4963 · Cited by 62
Detecting and quantifying social transmission using network‐based diffusion analysis
Hasenjager, M. J., Leadbeater, E., & Hoppitt, W. (2020) · Journal of Animal Ecology · doi:10.1111/1365-2656.13307 · Cited by 61
Lüpold, S., Reil, J. B., Manier, M. K., Zeender, V., Belote, J. M., & Pitnick, S. (2020) · Evolution Letters · doi:10.1002/evl3.193 · Cited by 62
Grace, J. K., & Anderson, D. J. (2014) · General and Comparative Endocrinology · doi:10.1016/j.ygcen.2014.08.020 · Cited by 61
Self-citationEcology and Economics of Using Native Managed Bees for Almond Pollination
Koh, I., Lonsdorf, E. V., Artz, D. R., Pitts‐Singer, T. L., & Ricketts, T. H. (2017) · Journal of Economic Entomology · doi:10.1093/jee/tox318 · Cited by 63
The Uncanny Valley Effect in Zoomorphic Robots
Löffler, D., Dörrenbächer, J., & Hassenzahl, M. (2020) · ACM/IEEE International Conference on Human-Robot Interaction (HRI) · doi:10.1145/3319502.3374788 · Cited by 61
“The Akaike Information Criterion (AIC) was calculated to select a model ([1], cited by [16]), because it penalizes the addition of parameters and thus selects the model with a minimum number of parameters.”
MethodEnvironmental and psychological variables influencing reactions to the COVID‐19 outbreak
Rubaltelli, E., Tedaldi, E., Orabona, N., & Scrimin, S. (2020) · British Journal of Health Psychology · doi:10.1111/bjhp.12473 · Cited by 61
Pest control of aphids depends on landscape complexity and natural enemy interactions
Martin, E. A., Reineking, B., Seo, B., & Steffan-Dewenter, I. D. (2015) · PeerJ · doi:10.7717/peerj.1095 · Cited by 71
“…and weights were calculated for each explanatory variable as the sum 291 of the AICc weights of each model it occurs in. Weights of each explanatory variable can thus be 292 interpreted as the probability of its presence, or importance, within the global averaged model 293 (Burnham et al. 2011).”
MethodShe’s a femme fatale: low-density larval development produces good disease vectors
Juliano, S. A., Sylvestre, G., Maciel‐de‐Freitas, R., Castro, M. G., Codeço, C. T., Lourenço‐de‐Oliveira, R., & Lounibos, L. P. (2014) · Memórias do Instituto Oswaldo Cruz · doi:10.1590/0074-02760140455 · Cited by 62
“All interactions were far from significant (p > 0.15) and this full model yielded a poorer information theoretic index [Akaike’s information criterion with a correction for small sample sizes (AICc)] (Burnham et al. 2011) than a reduced model with only main effects.”
MethodInfluentialMay, F., Giladi, I., Ristow, M., Ziv, Y., & Jeltsch, F. (2013) · Perspectives in Plant Ecology Evolution and Systematics · doi:10.1016/j.ppees.2013.08.002 · Cited by 61
Guerra, M., Dawson, S., Brough, T., & Rayment, W. (2014) · Endangered Species Research · doi:10.3354/esr00598 · Cited by 61
“Competing models were ranked with Akaike’s information criterion (AICc; Akaike 1973, Burnham et al. 2011).”
MethodManaging marine invasive species through public participation: Lionfish derbies as a case study
Malpica‐Cruz, L., Chaves, L. C. T., & Côté, I. M. (2016) · Marine Policy · doi:10.1016/j.marpol.2016.09.027 · Cited by 69
Step Rate Thresholds Associated with Moderate and Vigorous Physical Activity in Adults
O'Brien, M. W., Kivell, M. J., Wojcik, W. R., d’Entremont, G., Kimmerly, D. S., & Fowles, J. R. (2018) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph15112454 · Cited by 61
Wildlife roadkill patterns in a fragmented landscape of the Western Amazon
Filius, J., van der Hoek, Y., Jarrín–V, P., & van Hooft, P. (2020) · Ecology and Evolution · doi:10.1002/ece3.6394 · Cited by 61
The carbon sink of tropical seasonal forests in southeastern Brazil can be under threat
Maia, V. A., Santos, A. B. M., de Aguiar‐Campos, N., de Souza, C. R., de Oliveira, M. C. F., Coelho, P. A., Morel, J. D., da Costa, L. S., Farrapo, C. L., Fagundes, N. C. A., et al. (2020) · Science Advances · doi:10.1126/sciadv.abd4548 · Cited by 60
“Using multimodel inference, we averaged the coefficients of the selected models and used the conditional averaged coefficients as a final result ( 54 ).”
BackgroundMethodInfluentialEupen, C. V., Maes, D., Herremans, M., Swinnen, K. R., Somers, B., & Luca, S. (2021) · Ecological Modelling · doi:10.1016/j.ecolmodel.2021.109453 · Cited by 68
Noonan, M. J., Markham, A., Newman, C., Trigoni, N., Buesching, C. D., Ellwood, S. A., & Macdonald, D. W. (2014) · PLoS ONE · doi:10.1371/journal.pone.0083156 · Cited by 60
Latitudinal and bathymetrical species richness patterns in the NW Pacific and adjacent Arctic Ocean
Saeedi, H., Costello, M. J., Warren, D. L., & Brandt, A. (2019) · Scientific Reports · doi:10.1038/s41598-019-45813-9 · Cited by 60
González-Maya, J. F., Víquez‐R, L., Arias‐Alzate, A., Belant, J. L., & Ceballos, G. (2015) · Diversity and Distributions · doi:10.1111/ddi.12373 · Cited by 63
“We selected the best model using Akaike’s information criterion corrected for small samples (AICc; Burnham et al. (2011)) and Akaike weights (Wagenmakers & Farrell, 2004).”
MethodReproductive competition between females in the matrilineal Mosuo of southwestern China
Ji, T., Wu, J., He, Q.-Q., Jing-jing, X., Mace, R. H., & Tao, Y. (2013) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2013.0081 · Cited by 60
“We use a model selection approach [12,13] to investigate the determinants of the fertility (surviving children) and age at first birth of adult Mosuo women and men in duolocal households and mixed households (mixed household is a household in which parents are co-residents and all children are in duolocal marriages, c…”
MethodThe Early Shorebird Will Catch Fewer Invertebrates on Trampled Sandy Beaches
Schlacher, T. A., Carracher, L. K., Porch, N., Connolly, R. M., Olds, A. D., Gilby, B. L., Ekanayake, K. B., Maslo, B., & Weston, M. A. (2016) · PLoS ONE · doi:10.1371/journal.pone.0161905 · Cited by 60
“Model performance was evaluated using the corrected Akaike Information Criterion (AICc) based on all possible combinations of variables used in model building [29, 30].”
MethodMeyer, C. G., Anderson, J. M., Coffey, D. M., Hutchinson, M., Royer, M. A., & Holland, K. N. (2018) · Scientific Reports · doi:10.1038/s41598-018-23006-0 · Cited by 60
Villa, P. M., Martins, S. V., Neto, S. N. D. O., Rodrigues, A. C., Safar, N. V. H., Monsanto, L. D., Cancio, N. M., & Ali, A. (2018) · Ecological Indicators · doi:10.1016/j.ecolind.2018.08.005 · Cited by 60
Bell, J. R., Botham, M. S., Henrys, P. A., Leech, D. I., Pearce‐Higgins, J. W., Shortall, C. R., BRERETON, T. M., Pickup, J., & Thackeray, S. J. (2019) · Global Change Biology · doi:10.1111/gcb.14592 · Cited by 63
Species traits elucidate crop pest response to landscape composition: a global analysis
Tamburini, G., Santoiemma, G., O’Rourke, M. E., Bommarco, R., Chaplin‐Kramer, R., Dainese, M., Karp, D. S., Kim, T. N., Martin, E. A., Petersen, M. J., et al. (2020) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2020.2116 · Cited by 64
“A model in a set can be considered plausible if its ΔAICc is below 7 [33].”
Testing fit patterns with polynomial regression modelsPreprint
Schönbrodt, F. D. (2016) · doi:10.31219/osf.io/ndggf · Cited by 60
Biodiversity and pollination benefits trade off against profit in an intensive farming system
Scheper, J. A., Badenhausser, I., Kantelhardt, J., Kirchweger, S., Bartomeus, Í., Bretagnolle, V., Clough, Y., Gross, N., Raemakers, I., Vilà, M., et al. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2212124120 · Cited by 61
Insights from experimental economics on local cooperation in a small-scale fishery management system
Aswani, S., Gurney, G., Mulville, S., Matera, J., & Gurven, M. (2013) · Global Environmental Change · doi:10.1016/j.gloenvcha.2013.08.003 · Cited by 56
“Decreasing AIC values indicate increasing model parsimony relative to all other possible models in the set (Burnham et al., 2011; Johnson and Omland, 2004).”
BackgroundPhotosynthesis and isoprene emission from trees along an urban–rural gradient in Texas
Lahr, E. C., Schade, G. W., Crossett, C. C., & Watson, M. R. (2015) · Global Change Biology · doi:10.1111/gcb.13010 · Cited by 59
Elevated Immune Gene Expression Is Associated with Poor Reproductive Success of Urban Blue Tits
Capilla‐Lasheras, P., Dominoni, D. M., Babayan, S. A., O’Shaughnessy, P. J., Mladenova, M., Woodford, L., Pollock, C. J., Barr, T. A., Baldini, F., & Helm, B. (2017) · Frontiers in Ecology and Evolution · doi:10.3389/fevo.2017.00064 · Cited by 59
“Then, model selection based on Akaike’s Information Criterion (AIC, Burnham and Anderson, 2002; Burnham, 2004; Burnham et al., 2011) was applied to investigate alternative hypotheses on the effects of urban–forests conditions and of our experimental manipulation on immune gene expression, Frontiers…”
MethodHurisso, T. T., Culman, S. W., & Zhao, K. (2018) · Soil Science Society of America Journal · doi:10.2136/sssaj2018.03.0098 · Cited by 59
“Spatial autocorrelation was considered to be present when AIC of at least one of the semivariogram models that accounted for spatial correlations was lower than AIC from the null model that assumed no spatial autocorrelation (Burnham et al., 2011; Symonds and Moussalli, 2011).”
BackgroundInvasion of freshwater ecosystems is promoted by network connectivity to hotspots of human activity
Chapman, D. S., Gunn, I., Pringle, H., SIRIWARDENA, G. M., Taylor, P., Thackeray, S. J., Willby, N. J., & Carvalho, L. (2019) · Global Ecology and Biogeography · doi:10.1111/geb.13051 · Cited by 59
Noonan, M. J., Newman, C., Markham, A., Bilham, K., Buesching, C. D., & Macdonald, D. W. (2018) · Climatic Change · doi:10.1007/s10584-018-2248-5 · Cited by 58
Functional trait variation of forest understorey plant communities across Europe
Vanneste, T., Valdés, A., Verheyen, K., Perring, M. P., Bernhardt‐Römermann, M., Andrieu, É., Brunet, J., Cousins, S. A. O., Deconchat, M., SMEDT, P. D., et al. (2018) · Basic and Applied Ecology · doi:10.1016/j.baae.2018.09.004 · Cited by 58
Testing the effect of early‐life reproductive effort on age‐related decline in a wild insect
Rodríguez‐Muñoz, R., Boonekamp, J. J., Liu, X. P., Skicko, I. M., Fisher, D. N., Hopwood, P. E., & Tregenza, T. (2018) · Evolution · doi:10.1111/evo.13679 · Cited by 58
Early‐life seasonal, weather and social effects on telomere length in a wild mammal
van Lieshout, S. H. J., Badás, E. P., Ross, J. G. B., Bretman, A. J., Newman, C., Buesching, C. D., Burke, T. A., Macdonald, D. W., & Dugdale, H. L. (2021) · Molecular Ecology · doi:10.1111/mec.16014 · Cited by 57
“…and rainfall variability) best explained the variation in early- life RLTL (corrected Akaike information criterion [AICc] spring =1,133.1 was lowest, vs. summer ΔAICc =11.3, autumn ΔAICc =10.3, winter ΔAICc =11.0), with models with ΔAICc 7 from the top model being plausible (Burnham et al., 2011).”
MethodInfluentialImmunogenetic variation shapes the gut microbiome in a natural vertebrate population
Davies, C. S., Worsley, S. F., Maher, K. H., Komdeur, J., Burke, T. A., Dugdale, H. L., & Richardson, D. S. (2022) · Microbiome · doi:10.1186/s40168-022-01233-y · Cited by 59
“All models within seven AICc of the top model were included in the averaged model, to obtain the final conditional model [99].”
MethodPetelle, M. B., Martin, J. G. A., & Blumstein, D. T. (2015) · Journal of Evolutionary Biology · doi:10.1111/jeb.12700 · Cited by 58
Groenendijk, P., van der Sleen, P., Vlam, M., Bunyavejchewin, S., Bongers, F., & Zuidema, P. A. (2015) · Global Change Biology · doi:10.1111/gcb.12955 · Cited by 58
“Again, the model including the year effect differed slightly from the no-trend model (DAIC = 2.80), indicating that the detected trend was weak (cf. Burnham et al., 2011; Murtaugh, 2014).”
MethodInfluentialNatural disturbance reduces disease risk in endangered rainforest frog populations
Roznik, E. A., Sapsford, S. J., Pike, D. A., Schwarzkopf, L., & Alford, R. A. (2015) · Scientific Reports · doi:10.1038/srep13472 · Cited by 60
Marini, G., Guzzetta, G., Baldacchino, F., Arnoldi, D., Montarsi, F., Capelli, G., Rizzoli, A. P., Merler, S., & Rosà, R. (2017) · Parasites & Vectors · doi:10.1186/s13071-017-2041-8 · Cited by 58
França, F. M., Frazao, F. S., Korasaki, V., Louzada, J., & Barlow, J. (2017) · Biological Conservation · doi:10.1016/j.biocon.2017.10.014 · Cited by 60
Terrestrial mammal responses to oil palm dominated landscapes in Colombia
Pardo, L. E., Campbell, M. J., Edwards, W., Clements, G. R., & Laurance, W. F. (2018) · PLoS ONE · doi:10.1371/journal.pone.0197539 · Cited by 58
Lawn mowing frequency and its effects on biogenic and anthropogenic carbon dioxide emissions
Lerman, S. B., & Contosta, A. R. (2018) · Landscape and Urban Planning · doi:10.1016/j.landurbplan.2018.10.016 · Cited by 58
Cunningham, C. X., Johnson, C. N., & Jones, M. E. (2020) · Ecology Letters · doi:10.1111/ele.13473 · Cited by 62
Lolli, L., Batterham, A. M., Hawkins, R., Kelly, D. M., Strudwick, A. J., Thorpe, R. T., Gregson, W. A., & Atkinson, G. (2018) · British Journal of Sports Medicine · doi:10.1136/bjsports-2017-098884 · Cited by 58
Tong, S. X., He, X., & Deacon, S. H. (2016) · Memory & Cognition · doi:10.3758/s13421-016-0657-0 · Cited by 58
Between-Group Competition Impacts Reproductive Success in Wild Chimpanzees
Lemoine, S. R. T., Preis, A., Samuni, L., Boesch, C., Crockford, C., & Wittig, R. M. (2020) · Current Biology · doi:10.1016/j.cub.2019.11.039 · Cited by 58
“To compare the effect of the neighbor pressure index with the effect of the individual components of the index on survival during the pregnancy period, we conducted a model comparison based on Akaike information criterion (AIC) [27].”
MethodPersonal norms — and not only social norms — shape economic behavior
Bašić, Z., & Verrina, E. (2024) · Journal of Public Economics · doi:10.1016/j.jpubeco.2024.105255 · Cited by 63
Battisti, D. D., Fowler, M. S., Jenkins, S. R., Skov, M. W., Rossi, M., Bouma, T. J., Neyland, P. J., & Griffin, J. N. (2019) · Frontiers in Ecology and Evolution · doi:10.3389/fevo.2019.00150 · Cited by 57
Cunningham, C. X., Johnson, C. N., Hollings, T., Kreger, K., & Jones, M. E. (2019) · Ecography · doi:10.1111/ecog.04635 · Cited by 56
Diversity and patterns of marine non‐native species in the archipelagos of Macaronesia
Castro, N., Carlton, J. T., Costa, A. C., Marques, C. S., Hewitt, C. L., Cacabelos, E., Lopes, E. P., Gizzi, F., Gestoso, I., Monteiro, J. G., et al. (2022) · Diversity and Distributions · doi:10.1111/ddi.13465 · Cited by 56
Lee, T.-F., Yeh, S., Chao, P., Chang, L., Chiu, C.-L., Ting, H.-M., Wang, H., & Huang, Y.-J. (2015) · Radiation Oncology · doi:10.1186/s13014-015-0501-x · Cited by 56
“As a rule of thumb, ΔAIC = AICi – minAIC, whereas a ΔAIC >10 indicates that the model is very unlikely; values of 3–10 indicate that the model has considerably less support; values <2 suggest substantial evidence for the model and can be considered to be similar to the best model [30–32].”
Species or local environment, what determines the infection of rodents by Toxoplasma gondii?
Gotteland, C., Chaval, Y., Villena, I., Galan, M., Geers, R., Aubert, D., Poulle, M., Charbonnel, N., & Gilot‐Fromont, E. (2013) · Parasitology · doi:10.1017/s0031182013001522 · Cited by 59
“Akaike weights (wi) were used to obtain robust estimates of model parameters (Welch and MacMahon, 2005; Hobbs and Hilborn, 2006; Burnham et al. 2011).”
MethodGonzalez, J. H., Everaert, G., Boets, P., Galvis, A., & Goethals, P. L. M. (2013) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2013.06.004 · Cited by 56
“For defining sets of “best models” in the I-T approach, two criteria were considered: the models should have AICc differences (Di) lower than four units (Burnham et al., 2011) and they should have goodmodel performance (Symonds and Moussalli, 2011).”
MethodTick, B., Colvert, E., McEwen, F., Stewart, C., Woodhouse, E., Gillan, N., Hallett, V., Lietz, S., Garnett, T., Simonoff, E., et al. (2016) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2015.11.013 · Cited by 56
“direction of causation, the reciprocal (bidirectional) model is fitted first, and the unidirectional models (r and r’) are the nested sub-models compared by using likelihood ratio and fit statistics (Akaike Information Criterion [AIC] and Bayesian Information Criterion [BIC]).(40,41) Theoretically, if the variables on…”
MethodExploring plastic-induced satiety in foraging green turtles.
Santos, R., Andrades, R., Demetrio, G. R., Kuwai, G. M., Sobral, M. F., Vieira, J. D. S., & Machovsky-Capuska, G. (2020) · Environmental Pollution · doi:10.1016/j.envpol.2020.114918 · Cited by 45
Canale, N., Vieno, A., Doro, M., Rosa Mineo, E., Marino, C., & Billieux, J. (2019) · Scientific Reports · doi:10.1038/s41598-019-54911-7 · Cited by 50
Sumasgutner, P., SCHULZE, C. H., Krenn, H. W., & Gamauf, A. (2014) · Landscape and Urban Planning · doi:10.1016/j.landurbplan.2014.03.009 · Cited by 55
Signalling behaviour is influenced by transient social context in a spontaneously ovulating mammal
Owen, M. A., Swaisgood, R. R., Zhou, X., & Blumstein, D. T. (2015) · Animal Behaviour · doi:10.1016/j.anbehav.2015.10.008 · Cited by 55
“Because highly correlated predictor variables should not be considered in the same model (Burnham et al., 2011), we did not fit models that included additive or interactive effects for bleating and chirping vocalizations.”
BackgroundDavis, T. R., Champion, C., & Coleman, M. A. (2021) · Marine Environmental Research · doi:10.1016/j.marenvres.2021.105267 · Cited by 55
Copello, G. J., Diaz, L. E., & Orto, V. C. D. (2012) · Journal of Hazardous Materials · doi:10.1016/j.jhazmat.2012.03.045 · Cited by 55
Bonnot, N. C., Hewison, A. J. M., Morellet, N., Gaillard, J., Debeffe, L., Couriot, O. H., Cargnelutti, B., Chaval, Y., Lourtet, B., Kjellander, P., et al. (2016) · Animal Behaviour · doi:10.1016/j.anbehav.2016.11.031 · Cited by 55
A comprehensive allometric analysis of 2nd digit length to 4th digit length in humans
Lolli, L., Batterham, A. M., Kratochvíl, L., Jaroslav Flegr, A., Weston, K. L., & Atkinson, G. (2017) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2017.0356 · Cited by 55
“7, plausible alternative; 7-14, weak support; > 14, no empirical support [28].”
BackgroundSchaffnit, S. B., & Sear, R. (2017) · Population Studies · doi:10.1080/00324728.2017.1349924 · Cited by 57
“(For a fuller discussion of AIC model averaging and examples, see Burnham and Anderson 2002, 2004; Richards 2005; Alvergne et al. 2011; Borgerhoff Mulder and Beheim 2011; Burnham et al. 2011; Richards et al. 2011; Symonds and Moussalli 2011; Alvergne et al. 2013).”
BackgroundAustin, Å. N., Hansen, J. P., Donadi, S., & Eklöf, J. (2017) · PLoS ONE · doi:10.1371/journal.pone.0181419 · Cited by 55
“Models with less than 4 units of difference in AIC were assumed to fit the data equally well [55].”
Drivers of longitudinal telomere dynamics in a long‐lived bat species, Myotis myotis
Foley, N. M., PETIT, E. J., Brazier, T., Finarelli, J. A., Hughes, G. M., Touzalin, F., Puechmaille, S. J., & Teeling, E. C. (2020) · Molecular Ecology · doi:10.1111/mec.15395 · Cited by 57
Murphy, S. M., Cox, J. J., Clark, J. D., Augustine, B. C., Hast, J. T., Gibbs, D. B., Strunk, M., & Dobey, S. (2015) · Journal of Wildlife Management · doi:10.1002/jwmg.886 · Cited by 54
Mei, Z., de Groot, G. A., Kleijn, D., Dimmers, W. J., van Gils, S., Lammertsma, D. R., van Kats, R. J. M., & Scheper, J. A. (2021) · Agriculture Ecosystems & Environment · doi:10.1016/j.agee.2021.107570 · Cited by 56
Drummond‐Clarke, R. C., Kivell, T. L., Sarringhaus, L. A., Stewart, F. A., Humle, T., & Stewart, A. P. F. S. A. P. F. (2022) · Science Advances · doi:10.1126/sciadv.add9752 · Cited by 54
Landforms and soil attributes determine the vegetation structure in the Brazilian semiarid
Arruda, D. M., Schaefer, C. E. G. R., Corrêa, G. R., Rodrigues, P. M. S., Duque-Brasil, R., FERREIRAJR, W., & de Oliveira‐Filho, A. T. (2015) · Folia Geobotanica · doi:10.1007/s12224-015-9221-0 · Cited by 54
“The lower value of the second-order Akaike Information Criterion (AICc) was used, which indicates the most parsimonious model (Burnham et al. 2011).”
MethodLarge‐scale spatial variation in parasite communities influenced by anthropogenic factors
Altman, I., & Byers, J. E. (2014) · Ecology · doi:10.1890/13-0509.1 · Cited by 54
“We examined how much better the top model is compared to others in the set using an evidence ratio, this metric is calculated as the ratio between the likelihood of a given model and that of the overall best-performing model (Burnham et al. 2011).”
BackgroundMethodConservation implications of ameliorating survival of little brown bats with white‐nose syndrome
Maslo, B., Valent, M., Gumbs, J. F., & Frick, W. F. (2015) · Ecological Applications · doi:10.1890/14-2472.1 · Cited by 54
“To reduce model selection bias and uncertainty, we calculated estimates by averaging parameters within all models contributing to w 0.95 (Burnham and Anderson 2002, Burnham et al. 2011).”
MethodInfluentialMarine foraging ecology influences mercury bioaccumulation in deep-diving northern elephant seals
Peterson, S. H., Ackerman, J. T., & da Costa, D. P. (2015) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2015.0710 · Cited by 54
“0 [34].”
MethodConrad, J. L., Bibian, A. J., Weinersmith, K. L., Carion, D. D., Young, M. J., Crain, P., Hestir, E. L., Santos, M. J., & Sih, A. (2016) · Transactions of the American Fisheries Society · doi:10.1080/00028487.2015.1114521 · Cited by 54
“We compared candidate models with the Akaike information criterion (AIC), with the top-ranking model having the lowest AIC value (Burnham and Anderson 2002; Burnham et al. 2011).”
MethodBregović, P., & Zagmajster, M. (2016) · Insect Conservation and Diversity · doi:10.1111/icad.12164 · Cited by 55
“Due to substantial model selection uncertainty, we used multimodel inference and model averaging based on all models in the set (Burnham et al., 2011).”
MethodPyles, M. V., Júnior, J. A. D. P., Magnago, L. F. S., de Paula, A., & Meira‐Neto, J. A. A. (2018) · Biodiversity and Conservation · doi:10.1007/s10531-018-1598-7 · Cited by 57
Wildfire, national park visitation, and changes in regional economic activity
Kim, M., & Jakus, P. M. (2019) · Journal of Outdoor Recreation and Tourism · doi:10.1016/j.jort.2019.03.007 · Cited by 57
Arnold, J. M., Gerhardt, P., Steyaert, S. M. J. G., Hochbichler, E., & Hackländer, K. (2017) · Forest Ecology and Management · doi:10.1016/j.foreco.2017.10.050 · Cited by 54
Precipitation increases the abundance of fungal plant pathogens in Eucalyptus phyllosphere
Chen, Q., Hu, H., Yan, Z., Li, C., Nguyen, B. T., Zhu, Y., & He, J. (2021) · Environmental Microbiology · doi:10.1111/1462-2920.15728 · Cited by 53
Study on Raman multi-peak fitting and structure quantitative analysis of PAN-based carbon fibers
Wu, T., Lü, C., Sun, T., & Li, F. Y. (2022) · Journal of Materials Science · doi:10.1007/s10853-022-07589-8 · Cited by 53
“Here it is imperative to rescale AIC to [63]”
BackgroundMethodMoreira‐Arce, D., Vergara, P. M., Boutin, S. A., Carrasco, G., Briones, R., Soto, G. E., & Jiménez, J. E. (2016) · Forest Ecology and Management · doi:10.1016/j.foreco.2016.03.024 · Cited by 53
“We determined the level of support of each predictor variable by summing the Akaike weights (x) across all models that contained the variable of interest (x) (Burnham et al., 2010).”
MethodOptimal charging for general equivalent electrical battery model, and battery life management
Abdollahi, A., Han, X., Raghunathan, N., Pattipati, B., Balasingam, B., Pattipati, K. R., Bar‐Shalom, Y., & Card, B. (2016) · Journal of Energy Storage · doi:10.1016/j.est.2016.11.002 · Cited by 53
Quantitative histological models suggest endothermy in plesiosaurs
Fleischle, C. V., Wintrich, T., & Sander, P. M. (2018) · PeerJ · doi:10.7717/peerj.4955 · Cited by 54
Evans, D. R., Hobson, K. A., Kusack, J. W., Cadman, M. D., Falconer, C. M., & Mitchell, G. W. (2019) · Ibis · doi:10.1111/ibi.12727 · Cited by 53
Wang, J., Xu, R., & Xu, A. (2016) · The Journal of Chemical Thermodynamics · doi:10.1016/j.jct.2016.11.029 · Cited by 52
Briga, M., Jimeno, B., & Verhulst, S. (2019) · Experimental Gerontology · doi:10.1016/j.exger.2019.01.030 · Cited by 53
“To find the model best supported by the data we used the model selection approach proposed by Burnham and Anderson (Burnham and Anderson, 2002; Burnham et al., 2011) based on second order Akaike Information Criterion (AICc) with the function ‘dredge’ of the package ‘MuMIn’ version 1.40.4 (Barton,…”
InfluentialTaxonomic bias in amphibian research: Are researchers responding to conservation need?
da Silva, A. F., Malhado, A. C. M., Correia, R. A., Ladle, R. J., Vital, M. V. C., & Mott, T. (2020) · Journal for Nature Conservation · doi:10.1016/j.jnc.2020.125829 · Cited by 54
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.
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