How do I analyse data with 2 independent variables and 2 dependent variables? Im confused about what to do. I was thinking of running two seperate multiple regressions with a DV in each.. its after this, that I'm stuck. How do I see what effect the two DV's have combined? Or am I going about the whole thing wrong. Help!
My IV's are gender and group. 
My DV's will be scores on two seperate psychometric tests (likert scales)
I hope to have at least 100 people in each group (3 groups) so sample size will be roughly 300.
 A: Are you interested in examining the correlation between the dependent variables in the same model? I can't speak to the multiple independent variables part of the question, but you could investigate using a linear mixed model with multiple response variables (if your data will be longitudinal). I don't know of a website (I'm sure there is stuff out there, I just don't have a reference), but the book by Jeffrey Long, 'Longitudinal data analysis for the behavioral sciences using R' may be of use. Chapter 13 (p 501) has a section on models with multiple dv's.
A: You probably know about this, but I often start at this point:
http://www.ats.ucla.edu/stat/stata/whatstat/default.htm
A: You said "How do I see what effect the two DV's have combined". So, I believe your two DV's are somehow related based on theory. In this case, running independent equations each for one DV is totally wrong! Imagine you want to measure "speaking skill" and one of your DV's is "accuracy of talking" and the other one is "fluency of talking". In this respect, theory says that fluency and accuracy are related and are two sub-dimensions of the same concept-speaking skill. In this case, the two DV's should be considered together. Whenever it is the case, you have a continuous DV and categorical IV(s), Multivariate ANOVA (MANOVA) should be used. MANOVA is a variant of ANOVA that can incorporate multiple continuous DV's. Also, the number of IV's is irrelevant here as both ANOVA and MANOVA can accommodate 1 IV or 2 IV's or 3 IV's, etc. (called one way, two way, three-way etc. ANOVA or MANOVA)
Also, pay attention that MANOVA is a parametric test, meaning that your measurement must be continuous. it is hard to assume that measurement by any Likert-type scale with less than 7 anchors is continuous. 
