I want to do an analysis where my model contains 1 dependent variable which is continuous (eg. SCORE of respondents) and around 10 independent variables (eg- Age, income(continuous), Gender, disease status(binary), level of education, no. of working hours(categorical)). Will it be appropriate to use ANOVA?
Or should I use factorial ANOVA(i.e. Two-way ANOVA)? If none of them is appropriate, which method would be apt for this kind of model?
Best Answer
First of all, what is the purpose of your analysis is important.
If you want to evaluate the difference in scores (y) between the status of the disease (binary; 0 or 1), I recommend multiple linear regression in order to adjustment for confounding factors(age, income, gender, ...).
It is possible to estimate the difference in score between groups (disease status) adjusted for other covariates.