Abstract
The data analyst confronted with a large number of variables from which he must select a parsimonious subset, as independent variables in a multiple regression, is faced with a number of technical issues. What criterion should he use to judge the adequacy of his selection? What procedure should he use to select the subset of independent variables? How should he check for/guard against/correct for possible multicollinearity in his chosen set of independent variables?
“Stepwise regression can lead to confusing results...”
Daniel and Wood ([1980], p. 85)
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Madansky, A. (1988). Independent Variable Selection in Multiple Regression. In: Prescriptions for Working Statisticians. Springer Texts in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-3794-5_7
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