Fisher and Regression

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Fisher Lecture: Dimension Reduction in Regression (2007, background): “…little or no loss of information on Y |X. Model-based forward regression analyses traditionally condition on the observed values of the predictors, a characteristically Fisherian operation, even if X is random (see Savage, 1976, page 468, and Aldrich, 2005, for further discussion of this point).”
Models as Approximations I: Consequences Illustrated with Linear Regression (2014, background): “For the interesting history of ancillarity see the articles by Stigler (2001) and Aldrich (2005).”
ENVELOPE MODELS FOR PARSIMONIOUS AND EFFICIENT MULTIVARIATE LINEAR REGRESSION (2010, background): “This conditioning, common practice in regression, was discussed by Aldrich (2005) from an historical perspective.”
Models as Approximations - A Conspiracy of Random Regressors and Model Deviations Against Classical Inference in Regression (2015, background): “2014/07/30 file: Buja_et_al_Conspiracy-v2.tex date: July 23, 2015 MODELS AS APPROXIMATIONS 33 REFERENCES [1] Aldrich (2005).”