In my project, I am looking at the relationship between X and Y by the grouping factor "gender".
This is at two stages. The first is to see how XY correlate in each subgroup (Pearsons r) and the second is to see if there is a gender difference in the XY correlation (general linear model).
I am using SPSS and the scatter plot shows a linear relationship.
My sample comprises 60 males and 95 females.
Should I be correcting the effect of unbalanced design (i.e. different numbers in each subgroup) for my analyses?
I know Sum of Squares Type III corrects it for GLM but I am unsure about the bivariate correlation. (Does it matter for a correlation analysis?)
In response to the comments below:
I have used Probability Proportional to Size (PPS) cluster sampling and have taken into consideration the population distribution. For example, if the chosen entity has 700 members and half of them are females, I have strived to have this reflected in my sample.
I have inadvertently simplified the question above. I am testing two hypotheses. The first is to ascertain the relationship between X and Y. It is a simple bivariate correlation analysis. (Please ignore the first stage mentioned in the question above!). The second is to ascertain the effect of gender on the X-Y relationship.
- I have created the interaction term and I have included the main effects in my model.
My question again:
- Should I 'correct for' (unsure if this is the right terminology) for the different subgroup sizes in the X-Y correlation analysis? This is a simple bivariate correlation analysis. (i.e it has nothing to do with subgroup analysis by gender)
- Should I correct for the different subgroup sample sizes when doing the subgroup analysis by gender?