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Testing

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Abstract

This chapter considers two approaches to testing linear models. The approaches are identical in that a test under either approach is a well-defined test under the other. The two methods differ only conceptually. One approach is that of testing models; the other approach involves testing linear parametric functions.

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References

  • Casella, G., & Berger, R. L. (2002). Statistical inference (2nd ed.). Pacific Grove: Duxbury Press.

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  • Christensen, R. (1997). Log-linear models and logistic regression (2nd ed.). New York: Springer.

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  • Christensen, R. (2015). Analysis of variance, design, and regression: Linear modeling for unbalanced data (2nd ed.). Boca Raton: Chapman and Hall/CRC Press.

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  • Huynh, H., & Feldt, L. S. (1970). Conditions under which mean square ratios in repeated measurements designs have exact \(F\)-distributions. Journal of the American Statistical Association, 65, 1582–1589.

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  • Peixoto, J. L. (1993). Four equivalent definitions of reparameterizations and restrictions in linear models. Communications in Statistics, A, 22, 283–299.

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Correspondence to Ronald Christensen .

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Christensen, R. (2020). Testing. In: Plane Answers to Complex Questions. Springer Texts in Statistics. Springer, Cham. https://doi.org/10.1007/978-3-030-32097-3_3

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