7nov2011 - = 0 if treatment group 1 2 i X = 1 if treatment...

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CR Long C532: Regression Modeling 7 Nov 2011 1 Learning Objectives 1. Recognize when you need to create dummy variables to analyze data under the ANOVA model 2. Use the SPSS general linear model procedure to analyze data under the ANOVA model Review: ANOVA model represented as a simple linear regression model i i i X Y 1 0 , where X represents the explanatory variable that is the nominal categorical treatment group variable with 2 categories: i X = 1 if treatment group =1 and i X = 2 if treatment group =2 This does not hold if there are more than 2 categories of the explanatory variable. ANOVA model represented as a multiple linear regression model i j i j i i i X X X Y ) 1 ( ) 1 ( 2 2 1 1 0 ... , where X represents j- 1 new variables that represent the explanatory variable that is the nominal categorical treatment group variable with j levels. 1 i X = 1 if treatment group =1 and
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Unformatted text preview: = 0 if treatment group 1 , 2 i X = 1 if treatment group =2 and = 0 if treatment group 2, … ) 1 ( j i X = 1 if treatment group = j-1 and = 0 if treatment group j-1 These variables are referred to as dummy variables . There are j-1 dummy variables for a categorical explanatory variable with j levels. SPSS Regression>Linear procedure does not create dummy variables for categorical variables. You need to create them in your dataset. SPSS General Linear Models>Univariate procedure creates dummy variables for categorical variables you specify under Fixed Factor(s) . CR Long C532: Regression Modeling 7 Nov 2011 2 Using the SPSS procedure General Linear Model>Univariate will allow you to specify the explanatory variable as categorical by placing it under Fixed Factor(s):...
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This note was uploaded on 01/03/2012 for the course C 532 taught by Professor Long during the Fall '11 term at Palmer Chiropractic.

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7nov2011 - = 0 if treatment group 1 2 i X = 1 if treatment...

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