Abstract
Until now we have considered situations where the algebraic form of the model, i.e.,
was approximately correct. Obviously, this will not always be so. The actual relationship may not be a linear function of the \({x_{ij}}\)’s and sometimes not even of the β j ’s. In some such cases we may still be able to do linear regression by transforming (i.e., using functions of) the independent and/or the dependent variables.
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© 1990 Springer-Verlag New York Inc.
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Sen, A., Srivastava, M. (1990). Transformations. In: Regression Analysis. Springer Texts in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-4470-7_9
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DOI: https://doi.org/10.1007/978-1-4612-4470-7_9
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