An example to illustrate the question I have:
Suppose Strength is a function of gender (male/female) and, AMONG MALES, testosterone level (low, medium, or high). I don't care about testosterone levels in females, and those cells are blank for females in the data set.
If I were doing this through dummy coding, I would code this using four dummy variables: female, MaleLow, MaleMedium, MaleHigh.
strength = B1(female) + B2(MaleLow) + B3(MaleMed) + B4(MaleHigh)
To ask if sex matters, I would test mean strength of females vs weighted average of the 3 male categories.
To test if testosterone level matters, I want to test the null hypothesis that the mean strength in the 3 male categories is equal.
Can I do this using GLM without having to manually dummy code everything? if I put the categorical variable testosterone in the fixed factors, I am not sure how SPSS will handle it because this variable is only relevant to the male subset, and females all have missing values. How do I ask SPSS to test the specific hypothesis I am asking (if I'm correct, does B2=B3=B4, and does B1 = weighted average of B2,B3,B4)
The actual problem I have is a little more complex, in that the "females" have their own subcategories that are irrelevant to males, and there are additional categorical and continuous variables.