Hypothetical scenario. Let's say I'm running 6 separate ANCOVAs. My independent variable in each is field of study (3 groups: science, humanities, and business). For each ANCOVA my dependent variable is a different measure of IQ measured on a continuous scale (e.g., verbal score, math score, reading score, etc). In each ANCOVA there are two covariates: years of education (continuous variable) and sex (categorical variable). Let's say that I'm considering assumptions for each of the 6 ANCOVAs to determine whether running an ANCOVA is appropriate, and let's say that in 4 of the 6 cases I determine that running an ANCOVA is not appropriate: let's say in one instance I violate the homogeneity of regression assumption, in another instance I violate the homoscedasticity assumption (based on looking at plots )of the standardized residuals against the predicted values, in another instance I violate the assumption that the residual are normally distributed for each level of the independent variable, and in a fourth instance I determine based on past literature that my age covariate likely won't be linearly related to my dependent variable at one or more levels of my independent variable. I looked online for a nonparametric test I can run in place of ANCOVA and I found something called Quade's test, and I found some instruction on how to run it in SPSS. However I can't find anywhere online what the assumptions are for the test. So I'm wondering what the assumptions are for Quade's test so I can determine if I can run Quade's test in any or all of the four instances described above in which I violated one of the assumptions for ANCOVA.
Thanks much in advance! FBH