Alternative Tests for the Selection of Model Variables (Classic Reprint) - Hardcover

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Excerpt from Alternative Tests for the Selection of Model Variables

One of the most difficult and subtle tasks confronting the mathematical model-builder is the selection of appropriate variables and functional relationships for his model. In specifying each equation, the modeler faces two distinct problems. First, he must posit a priori hypotheses about the variables or factors which he believes are impor tant causes of change in the dependent variable of that equation. Sec ond, once such hypotheses have been advanced, the modeler must have some means of testing whether or not, given the available empirical information, those variables which a priori reasoning has led him to consider should be included in the model. Based on the results of such testing, the modeler may be led to reject certain variables as being relatively unimportant, and may thereby begin to refine his initial causal hypotheses.

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