I am completing a project for a client using general linear model (GLM command) in SPSS/PASW (Ver. 17)
Basically, the project is designed to find out if factors such as gender and age affect the relationship between Variables A and B.
In this case,
- Variable A is the independent variable (IV)
- Variable B is the dependent variable (DV)
- Gender or age are the factors
In GLM command, IV goes in the covariate box and gender goes in the factor box.
Many textbooks I have consulted say one of two things (generally):
- GLM can be used to assess the joint significance of the predictors (A and gender in the above example) on a continuous outcome (B in the above example)
- GLM can be used to assess the significance of the factor (gender in the above example) on the outcome (B in the above example) by controlling for the effect of the covariate (A in the above example).
Obviously, these two different usages lead to different outcomes. I am interested in the joint significance.
I find the above a bit contradictory but I am not statistically trained. Can any one explain the key difference above (when the same test is in question i.e. IV in the covariate box and gender in the factor box).