Multiple Regression Analysis - SAGE Publications Inc

157 CHAPTER 5 AMultiple Regression General ConsiderationsMultiple Regression Analysis , a term first used by Karl Pearson (1908), is an extremely useful extension of simple linear Regression in that we use several quantitative (metric) or dichotomous variables in combination rather than just one such variable to predict or explain the value of a quantitatively mea-sured criterion (outcome/dependent) variable. Most researchers believe that using more than one predictor or potentially explanatory variable can paint a more complete picture of how the world works than is permitted by simple linear Regression because behavioral scientists generally believe that behav-ior, attitudes, feelings, and so forth are determined by Multiple variables rather than just one.

such a label that includes the term “statistical” may seem a little odd (of course regression is a statisti-cal procedure), but the label is meant to communicate something rather important but subtle regard-ing the analysis procedures. The reason for calling the procedures “statistical regression methods” is to

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