Calculate Interaction Term in SPSS

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Calculate Interaction Term in SPSS

R Duke
Hello SPSS Experts, 

I apologize for the novice question but I have 3 independent variables (A, B, and C) that are highly correlated and I want to calculate the interaction term for these 3 variables (one DV within). I am new to SPSS and I'm not sure how to calculate the interaction between A*B*C. I have included some mock data below and would appreciate any help. 

Cheers, 

R

0.78

0.62

0.39

0.80

0.98

0.83

0.51

0.42

0.39

0.45

0.60

0.20

0.35

0.53

0.37

0.12

0.58

0.12

0.40

0.43

0.28

0.57

0.84

0.55

0.86

0.68

0.42

0.45

0.21

0.14

0.57

0.53

0.45

0.29

0.37

0.17

0.48

0.81

0.45

0.76

0.44

0.24

0.54

0.62

0.30

0.07

0.06

0.06

0.42

0.92

0.66

0.92

0.91

0.92

0.70

0.76

0.44

1.00

0.25

0.09

0.45

0.45

0.23

0.81

1.00

1.00

0.02

0.53

0.25

0.49

0.91

0.56

0.25

0.58

0.35

0.00

0.00

0.00


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Re: Calculate Interaction Term in SPSS

Maguin, Eugene
R,
 
If A, B, and C are highly correlated, you have to assume that you will have collinearity problems. So, you'll need to monitor that in the analysis. That said, I'd center each variable by subtracting it's mean and then simply multiply A*B*C. (As well as A*B, A*C, and B*C). I assume you are doing a regression of some kind so you're final eqation will have seven terms plus the constant (A, B, C, A*B, A*C, B*C, and A*B*C). I would use the centered versions of A, B, and C rather than the raw score versions.
 
Gene Maguin
 
 
 


From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of R Duke
Sent: Thursday, February 03, 2011 5:46 PM
To: [hidden email]
Subject: Calculate Interaction Term in SPSS

Hello SPSS Experts, 

I apologize for the novice question but I have 3 independent variables (A, B, and C) that are highly correlated and I want to calculate the interaction term for these 3 variables (one DV within). I am new to SPSS and I'm not sure how to calculate the interaction between A*B*C. I have included some mock data below and would appreciate any help. 

Cheers, 

R

0.78

0.62

0.39

0.80

0.98

0.83

0.51

0.42

0.39

0.45

0.60

0.20

0.35

0.53

0.37

0.12

0.58

0.12

0.40

0.43

0.28

0.57

0.84

0.55

0.86

0.68

0.42

0.45

0.21

0.14

0.57

0.53

0.45

0.29

0.37

0.17

0.48

0.81

0.45

0.76

0.44

0.24

0.54

0.62

0.30

0.07

0.06

0.06

0.42

0.92

0.66

0.92

0.91

0.92

0.70

0.76

0.44

1.00

0.25

0.09

0.45

0.45

0.23

0.81

1.00

1.00

0.02

0.53

0.25

0.49

0.91

0.56

0.25

0.58

0.35

0.00

0.00

0.00


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Re: Calculate Interaction Term in SPSS

Maurice Vergeer
there's a difference between regular collinearity and collinearity due to interaction terms. The first is really problematic, the second refers to inflated standard error because these are conditional ones (if I remember correctly).
There is a very good article on this matter by Friedrichs (1982) : http://faculty.fuqua.duke.edu/~charlesw/s591/Methods/c09_Bennet/Friedrich_AJPS_82.pdf.

Maurice





On Fri, Feb 4, 2011 at 15:37, Gene Maguin <[hidden email]> wrote:
R,
 
If A, B, and C are highly correlated, you have to assume that you will have collinearity problems. So, you'll need to monitor that in the analysis. That said, I'd center each variable by subtracting it's mean and then simply multiply A*B*C. (As well as A*B, A*C, and B*C). I assume you are doing a regression of some kind so you're final eqation will have seven terms plus the constant (A, B, C, A*B, A*C, B*C, and A*B*C). I would use the centered versions of A, B, and C rather than the raw score versions.
 
Gene Maguin
 
 
 


From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of R Duke
Sent: Thursday, February 03, 2011 5:46 PM
To: [hidden email]
Subject: Calculate Interaction Term in SPSS

Hello SPSS Experts, 

I apologize for the novice question but I have 3 independent variables (A, B, and C) that are highly correlated and I want to calculate the interaction term for these 3 variables (one DV within). I am new to SPSS and I'm not sure how to calculate the interaction between A*B*C. I have included some mock data below and would appreciate any help. 

Cheers, 

R

0.78

0.62

0.39

0.80

0.98

0.83

0.51

0.42

0.39

0.45

0.60

0.20

0.35

0.53

0.37

0.12

0.58

0.12

0.40

0.43

0.28

0.57

0.84

0.55

0.86

0.68

0.42

0.45

0.21

0.14

0.57

0.53

0.45

0.29

0.37

0.17

0.48

0.81

0.45

0.76

0.44

0.24

0.54

0.62

0.30

0.07

0.06

0.06

0.42

0.92

0.66

0.92

0.91

0.92

0.70

0.76

0.44

1.00

0.25

0.09

0.45

0.45

0.23

0.81

1.00

1.00

0.02

0.53

0.25

0.49

0.91

0.56

0.25

0.58

0.35

0.00

0.00

0.00





--
___________________________________________________________________
Maurice Vergeer
Department of communication
Radboud University  (www.ru.nl)
PO Box 9104
NL-6500 HE Nijmegen
The Netherlands

Visiting Professor Yeungnam University, Gyeongsan, South Korea

contact:
E: [hidden email]
T: +31 24 3612297 (direct)/ 3612372 (secretary) / maurice.vergeer (skype)
personal webpage: www.mauricevergeer.nl
blog:  http://blog.mauricevergeer.nl/
Journalism: www.journalisteninhetdigitaletijdperk.nl

Recent publications (see complete list at www.mauricevergeer.nl/node/2):
-Vergeer, M., Hermans, L., & Sams, S. (accepted for publication). Online social networks and micro-blogging in political campaigning: The exploration of a new campaign tool and a new campaign style. Party Politics.
-Eisinga, R., Franses, Ph.H., & Vergeer, M. (2010). Weather conditions and daily television use in the Netherlands, 1996–2005. International Journal of Meteorology.
___________________________________________________________________