I'm working on a research project testing the social control theory of delinquency set out by Hirschi (1969). I have two separate dependent delinquency variables (one for minor and one for serious delinquency) which are standardized scores and three variables which measure social control and have been entered as covariates (two dichotomous variables and one scale). I then also have 8 independent varaiables on such background info as age, gender, level of domestic discord, family structure, etc. I need help constructing a MANOVA as my box test and levene's test both indicate I have violated assumptions. The problem is that my outliers represent truly significant different groups from the norm and and I do not wish to delete them; furthermore, delinquency is not a normally distributed phenomenon and so transforming the variables would be manipulating the data too much. I have already conducted logistic and standard linear regressions to examine the relationship between the three types of variables (independent, intervening, dependent) but now want to take it to the next level of analysis where they are all included in one model which will take into account interactions. Is there any other way to decided which variables can be excluded from the analysis? I am really stuck and my dissertation is due next week!

Thanks,

J