In my study, participants saw a picture of a man or woman either with or without a cigarette. So I have a 2(Male, Female) x 2(Smoker, Non-smoker) experimental design.
Coding: Male=1, Female=2, Smoker=1 and Non-Smoker=2
The question is whether participants would choose to (1) Date, (2) Not Date or (3) Become Friends (with the person on the picture).
I have put Gender and Smoking Status into the Co-Variate Box in SPSS and put the DV into the DV-Box with (2) Not Date as a reference category.
I used a cutomized model, that is, I put Gender, Smoking Status and Gender*Smoking Status into the model by using the forced-entry method.
After analyzing the data I found an interaction effect for "Date vs. No Date":
b= -1.56, Exp(B)= .340, p= .034.
Questions:
Based on these coefficients, would I be able to interpret the interaction effect? (I don't know how to do this).
Or would I need to do follow-ups to see if there are simple main effects?
Best Answer
An interaction effect means that the relationship between the DV and the IV is different at different levels of the other IV. So, the effect of smoking is different for men and women and the effect of sex is different for smokers and nonsmokers.
You should (very nearly) always include the main effects when you include an interaction
The easiest way to see what is going on is to get the predicted probabilities of each combination. I don't know how to do this in SPSS, but there is surely a way. Different programs code the dependent variable differently and this can reverse the meaning of the interaction.