Transcription of MULTIPLE REGRESSION WITH CATEGORICAL DATA
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MULTIPLE REGRESSION WITH CATEGORICAL DATA
ISexMerit PayiSexMerit OF POLITICAL SCIENCEANDINTERNATIONAL RELATIONSPosc/Uapp 816 MULTIPLE REGRESSION WITH CATEGORICAL DATA REGRESSION with CATEGORICAL : Agresti and Finlay Statistical Methods in the Social Sciences, 3rdedition, Chapter 12, pages 449 to INDEPENDENT : what does sex discrimination in employment mean and how can it bemeasured? answer these questions consider these artificial data pertaining to employmentrecords of a sample of employees of Ace : here the dependent variable, Y, is merit pay increase measured in percentand the "independent" variable is sex which is quite obviously a nominal orcategorical goal is to use CATEGORICAL variables to explain variation in Y, a quantitativedependent need to convert the CATEGORICAL variable gender into a form that makessense to REGRESSION way to represent a CATEGORICAL variable is to code the categories 0 and 1 asfollows:Posc/Uapp 816 Class 14 MULTIPLE REGRESSION With CATEGORICAL DataPage 2let X = 1 if sex is "male"0 otherwiseiSexMerit PayiSex Merit Pay (c1) (c2) (c3) (c1) (c2) (c3) : Bob is scored "1" because he is male.
Here is a partial regression ANOVA table: Posc/Uapp 816 Class 14 Multiple Regression With Categorical Data Page 5 6. At the .05 level, the critical value of F with 1 and 8 degrees of freedom is 5.32. Thus, the observed F is barely significant. Since the critical F at the
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