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CD03 Moderation AnalysisVariable Name: X1X2X3YZ
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Note! This example only works when X2 is a DICHOTOMOUS VARIABLE CODED 0 and 1! The data is at the top right by "Variable Name", Variable Explanation:Variable 1Variable 2Interaction VariableResult / ImpactModerator of the relationship between X and Y
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Data Type:RatioNominal?Ratio
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Variable Coding:Years on the jobSex (Men - 0; Women = 1)YearsOnJob(X1)*Sex(X2);Salary in $1000s
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Result:Male0
Equals YearsOnJob if X2 is Female; Zero for all other possibilities (1. 0 Years on Job; 2. X2 Female; x Years on Job, X2 is Male, 3. 0 years on Job, X2 is male)
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Female1
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Y' = 55.0 + 1.5X1 -3.4X2 + .7X3
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The predicted Salary in $1000s for a Male with zero Years on the job55
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The predicted gain in Salary in $1000s for extra Years on the job for a Male or Female1.5*X1
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The modeled difference in Salary in $1000s between Male and Female who have zero Years on the job-3.4*X2
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The additional gain in Salary in $1000s for each of the Years on the job above zero for Female's0.7*X3
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Sex (Men - 0; Women = 1)Female<- X2Checksum:
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Years on the job2<- X1
For Men, ŷ=Intercept+Bsub1*x1
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1 if Sex=Female, 0 for all others. 2<- X3 (Interaction)
For Women, ŷ=Intercept-Bsub2+(Bsub1+Bsub3)*xone
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Predicted Y = Y' = 53
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Table:
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X1 Values: MaleFemale
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05551.63.4
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Male 37 years experience:258562
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Female 37 years experience:46160.40.6
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Male with 5 Years Experience.. . 66464.8-0.8
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66464.8-0.8
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208595.6-10.6
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