Model averaging and muddled multimodel inferences

Ecology

Volumn 96, Issue 9, 2015, Pages 2370-2382

  Cade, Brian S ^a  

^a U S GEOLOGICAL SURVEY   (United States)

Author keywords

Generalized linear models; Greater Sage Grouse; Model averaging; Multicollinearity; Multimodel inference; Partial effects; Partial standard deviations; Regression coefficients; Relative importance of predictors; Species distribution models; Zero truncated Poisson regression

Indexed keywords

AKAIKE INFORMATION CRITERION; BIRD; DATA INTERPRETATION; ECOLOGICAL APPROACH; MODEL VALIDATION; POISSON RATIO; PREDICTION; REGRESSION ANALYSIS; SPATIAL DISTRIBUTION;

COLORADO; UNITED STATES;

CENTROCERCUS UROPHASIANUS;

ANIMAL; ANIMAL DISPERSAL; BIOLOGICAL MODEL; GALLIFORMES; PHYSIOLOGY; UNITED STATES;

ANIMAL DISTRIBUTION; ANIMALS; COLORADO; GALLIFORMES; MODELS, BIOLOGICAL;

EID: 84932194664     PISSN: 00129658     EISSN: 19399170     Source Type: Journal    
DOI: 10.1890/14-1639.1     Document Type: Article

References (49)

1. Aho, K., D. Derryberry, and T. Peterson. 2014. Model selection for ecologists: the worldviews of AIC and BIC. Ecology 95: 631-636.
2. Aitchison, J. 1986. The statistical analysis of compositional data. Chapman and Hall, London, UK.
3. Aitchison, J., and J. J. Egozcue. 2005. Compositional data analysis: Where are we and where should we be heading? Mathematical Geology 37:829-850.
4. Blums, P., J. D. Nichols, J. E. Hines, M. S. Lindberg, and A. Mednis. 2005. Individual quality, survival variation and patterns of phenotypic selection on body condition and timing of nesting in birds. Oecologia 143:365-376.
5. Bring, J. 1994. How to standardize regression coefficients. American Statistician 48:209-213.
6. Burnham, K. P., and D. R. Anderson. 1998. Model selection and inference: a practical information-theoretic approach. Springer-Verlag, New York, New York, USA.
7. Burnham, K. P., and D. R. Anderson. 2002. Model selection and multimodel inference: a practical information-theoretic approach. Springer-Verlag, New York, New York, USA.
8. Burnham, K. P., and D. R. Anderson. 2004. Multimodel inference: understanding AIC and BIC in model selection. Sociological Methods and Research 33:261-304.
9. Burnham, K. P., and D. R. Anderson. 2014. P values are only an index to evidence: 20th- vs. 21st-century statistical science. Ecology 95:627-630.
10. Burnham, K. P., D. R. Anderson, and K. P. Huyvaert. 2011. AIC model selection and multimodel inference in behavioral ecology: some background, observations, and comparisons. Behavioral Ecology and Sociobiology 65:23-35.
11. Candolo, C., A. C. Davison, and C. G. B. Demetrio. 2003. A note on model uncertainty in linear regression. Statistician 52 (Part 2):165-177.
12. Chamberlin, T. C. 1890. The method of multiple working hypotheses. Science 15:92-96
13. reprinted 1965 Science 148: 754-759.
14. Chevan, A., and M. Sutherland. 1991. Hierarchical partitioning. American Statistician 45:90-96.
15. Christensen, R. 1992. Comments on Chevan and Sutherland. American Statistician 46:74.
16. Copas, J. B. 1983. Regression, prediction, and shrinkage. Journal of the Royal Statistical Society, Series B (Methodological) 45:311-354.
17. Doherty, P. F., G. C. White, and K. P. Burnham. 2012. Comparison of model building and selection strategies. Journal of Ornithology 152:S317-S323.
18. Dormann, C. F., et al. 2013. Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography 36:27-46.
19. Draper, D. 1999. Comment - Bayesian model averaging: a tutorial. Statistical Science 14:405-409.
20. Elith, J., and J. R. Leathwick. 2009. Species distribution models: ecological explanation and prediction across space and time. Annual Review of Ecology, Evolution, and Systematics 40:677-697.
21. Fox, J., and G. Monette. 1992. Generalized collinearity diagnostics. Journal of the American Statistical Association 87:178-183.
22. Franklin, J. 2009. Mapping species distributions: spatial inference and prediction. Cambridge University Press, Cambridge, UK.
23. Franklin, J. 2013. Species distribution models in conservation biogeography: developments and challenges. Diversity and Distributions 19:1217-1223.
24. Freckleton, R. P. 2011. Dealing with collinearity in behavioural and ecological data: model averaging and the problems of measurement error. Behavioral Ecology and Sociobiology 64: 91-101.
25. Frisch, R., and F. V. Waugh. 1933. Partial time regressions as compared with individual trends. Econometrica 1:387-401.
26. Galipaud, M., M. A. F. Gillingham, M. David, and F.-X. Dechaume-Moncharmont. 2014. Ecologists overestimate the importance of predictor variables in model averaging: a plea for cautious interpretations. Methods in Ecology and Evolution 5:983-991.
27. Giudice, J. H., J. R. Fieberg, and M. S. Lenarz. 2012. Spending degrees of freedom in a poor economy: a case study of building a sightability model for moose in northeastern Minnesota. Journal of Wildlife Management 76:75-87.
28. Graham, M. H. 2003. Confronting multicollinearity in ecological multiple regression. Ecology 84:2809-2815.
29. Grömping, U. 2007. Estimators of relative importance in linear regression based on variance decomposition. American Statistician 61:139-147.
30. Grueber, C. E., S. Nakagawa, R. J. Laws, and I. G. Jamieson. 2011. Multimodel inference in ecology and evolution: challenges and solutions. Journal of Evolutionary Biology 24:699-711.
31. Harrell, F. E., Jr. 2001. Regression modeling strategies: with applications to linear models, logistic regression, and survival analysis. Springer-Verlag, New York, New York, USA.
32. Hobbs, N. T., and R. Hilborn. 2006. Alternatives to statistical hypothesis testing in ecology: a guide to self teaching. Ecological Applications 16:5-19.
33. Hoeting, J. A., D. Madigan, A. E. Raftery, and C. T. Volinsky. 1999. Rejoinder - Bayesian model averaging: a tutorial. Statistical Science 14:412-417.
34. Hron, K., P. Filzmoser, and K. Thompson. 2012. Linear regression with compositional explanatory variables. Journal of Applied Statistics 39:1115-1126.
35. Jensen, J. L. W. V. 1906. Sur les fonctions convexes et les inéagalitiés entre les valeurs moyennes. Acta Mathematica 30:175-193.
36. Johnson, J., and K. Omland. 2004. Model selection in ecology and evolution. Trends in Ecology and Evolution 19:101-108.
37. Knick, S. T., and J. W. Connelly. 2011. Greater sage-grouse and sagebrush: an introduction to the landscape. Pages 1-12 in S. T. Knick and J. W. Connelly, editors. Greater sagegrouse ecology and conservation of a landscape species and its habitats. Studies in avian biology. Volume 38. University of California Press, Berkley, California, USA.
38. Kruskal, W., and R. Majors. 1989. Concepts of relative importance in recent scientific literature. American Statistician 43:2-6.
39. Lovell, M. C. 1963. Seasonal adjustment of economic time series and multiple regression analysis. Journal of the American Statistical Association 58:993-1010.
40. Lukacs, P. M., K. P. Burnham, and D. R. Anderson. 2010. Model selection bias and Freedman's paradox. Annals of the Institute of Statistical Mathematics 62:117-125.
41. MacNally, R. 2000. Regression model-building in conservation biology, biogeography and ecology: the distinction between - and reconciliation of - 'predictive' and 'explanatory' models. Biodiversity and Conservation 9:655-671.
42. Murray, K., and M. M. Conner. 2009. Methods to quantify variable importance: implications for the analysis of noisy ecological data. Ecology 90:348-355.
43. Murtaugh, P. A. 2014a. In defense of P values. Ecology 95:611-617.
44. Murtaugh, P. A. 2014b. Rejoinder. Ecology 95:651-653.
45. Neter, J., M. H. Kutner, C. J. Nachtsheim, and W. Wasserman. 1996. Applied linear statistical models. Fourth edition. Richard D. Irwin, Chicago, Illinois, USA.
46. Rice, M. B., A. D. Appa, M. L. Phillips, J. H. Gammonley, B. P. Petch, and K. Eichoff. 2013. Analysis of regional species distribution models based on radio-telemetry datasets from multiple small-scale studies. Journal of Wildlife Management 77:821-831.
47. Schroeder, M. A., et al. 2004. Distribution on sage-grouse in North America. Condor 106:363-376.
48. Spanos, A. 2014. Recurring controversies about P values and confidence intervals revisited. Ecology 95:645-651.
49. Tibshirani, R. 1996. Regression shrinkage and selection via the lasso. Journal Royal Statistical Society B 58:267-288.