I am trying to fit a model to predict a quantitative response variable, using several binary variables. In particular, I am interested in measuring the relationship between one of the binary variables and the outcome variable, holding the other binary variables constant.
My inclination is that ANOVA is the appropriate method to use. The advantage of ANOVA over a series of t-tests should be avoiding Type 1 errors. But I seem to recall from stats that ANOVA is primarily designed for predictor variables with more than 2 levels, aka not binary.
Which is preferable?
Final question: is there any reason not to use multiple regression in this case? Thanks.