How to get rid of heterogeneity of regression slopes using multilevel modeling? I have problem with homogeneity of regression slopes in ANCOVA. I have two species of snakes and I want to compare their tail lengths (dependent variable), that are dependent on body length (in ANCOVA used as covariate). Other ANCOVA assumptions are met, but there exist significant interaction between species*bodylength (intercepts are comparable, slopes are different). 
Andy Field´s SPSS guide tells that broken assumption of homogeneity of regression slopes could be cast aside using multilevel statistic model. I´m trying to correctly run this analysis whole day, but I am unable to do it. Problem is that I want to compare tail lengths between species, which is my top of hierarchy (at the bottom are individual specimen). Do I have to set variable species as subject (assuming some hierarchy)? 
Undoubtely I have to set body length as covariate and tail length as dependent variable. How can I compare my groups (species) independently of slopes (slopes are random)? What should be set as fixed factors and what random factors in SPSS? Field´s guide also tells that for mixed model analysis there is bug (version 17.0) related to factors dialog box such that categorical variables (in this case my species variable) should be put into covariate box (at least if it is bivariate). Is he right? I know what I want to do but dont know how to do it. 
 A: You could simply create interaction terms between your predictor (body length) and an indicator variable for the species (that is, species fixed effects). You would then regress your outcome (tail length) on the species fixed effects and the interactions terms. My coauthors and I detail this procedure in our paper, Broken or Fixed Effects?
A: I think it is possible to code specie specific slopes using your data and enter them into your model. You said you have only 2 species so a multilevel specification may not be needed. 
I have performed a multilevel analysis 1 time in SPSS (yes, not via the GUI but Syntax) but I do not know how it works with ANCOVA. 
A: If what you want is to compare de ADJUSTED means of tail length at a fixed covariate (in order to remove the effect of total size), it is necessary to run an ANCOVA as you have explained and did. However if the homogeneity of slopes do not apply to your data IT MEANS something that is biologically interesting, something like the length of the tail among species varies when comparing different sizes of snakes. One option will be to make a scatterplot, test the interaction covXspecies to see if the you have heterogeneity of slopes and then describe the differences using the scaterplot. Other option could be to make size categories of body length in order to remove influence of covariates on response variable and treat it as a fixed factor. You will have then a 2 way ANOVA with species and size category as fixed factors. then you migth be able to test for interaction between species and size which i think it is most interesting than just testing for differences among species. did it help?, please excuse my english! 
