2.S: Fitting Statistical Models to Data (Summary)

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Footnotes

1: I assume here that you have little interest in organisms other than lizards.

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2: And, often, concludes that we just "need more data" to get the answer that we want.

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3: Especially in fields like genomics where multiple testing and massive Bonferroni corrections are common; one can only wonder at the legions of type II errors that are made under such circumstances.

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References

Akaike, H. 1998. Information theory and an extension of the maximum likelihood principle. Pp. 199–213 in E. Parzen, K. Tanabe, and G. Kitagawa, eds. Selected papers of Hirotugu Akaike. Springer New York, New York, NY.

Burnham, K. P., and D. R. Anderson. 2003. Model selection and multimodel inference: A practical information theoretic approach. Springer Science & Business Media.

Edwards, A. W. F. 1992. Likelihood. Johns Hopkins University Press, Baltimore.

Gelman, A., J. B. Carlin, H. S. Stern, D. B. Dunson, A. Vehtari, and D. B. Rubin. 2013. Bayesian data analysis, third edition. Chapman; Hall/CRC.

Neal, R. 2008. The harmonic mean of the likelihood: Worst Monte Carlo method ever. Radford Neal’s blog.

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