Modeling Relationships of Multiple Variables with Linear Regression
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| effects - the interplay among factors on predicted outcomes. For instance, regression models can predict the expected GPAs based on combinations of variables as they maybe configured in the lives of individuals (e.g., a non-drinking, female, athlete. They also can measure the amount of variation in the dependent variable that can be attributed to the variables in the model, and conversely, how much of the variation is left unexplained. In the case of GPAs, a regression model can tell the strength of the six factors in predicting academic success. Do these factors account for many of the differences among students, or only a small fraction of the differences Regression models measure explanatory power, and how well predictions of social behavior correspond with observations of social behavior. Additionally, multiple regression models are critical to accounting for the potential impact of spurious relationships. Recall from Chapter 1 that a spurious relationship occurs when a third variable creates the appearance of relationship between two other variables, but this relationship disappears when that third variable is included in the analysis. Using the example above, perhaps the differences in performances of athletes and non- athletes may simply be the result of athletes spending less time studying. If the negative association of athletics to GPA disappears when studying is taken into account, it leads to a Chapter 7 • Modeling Relationships of Multiple Variables with Linear Regression 163 more sophisticated understanding of social behavior, and more informed policy recommendations. Finally, one of the great advantages of mulitple regression models is that they allow for the inclusion of control variables. Control variables not only help researchers account for spurious relationships, they measure the impact of any given variable above and beyond the effects of other variables. For example, a researcher could document the influence of drinking on GPAs adjusting for the impact of gender, sports, fraternities, and time spent studying. Or consider the relationship between gender and GPA. Suppose the relationship between gender and GPA disappears after taking into account all of the other variables in the model. What would that suggest about theories that posit innate differences inabilities to succeed in college Download 0.6 Mb. Share with your friends:
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