I am aware that one should transform percentages and proportions when using them in an ANOVA, due to the values being bounded by 0 and 1. I have seen suggestions that the best transformations are logit and arcsine (with benefits/problems with both).
However, I have two linked questions about a multiple linear regression.
1) Does one still need to transform the percentages and proportions when using them as predictor variables in a multiple linear regression? Or can they be left in their raw form?
2) How about when using percentages/proportions as an outcome variable in a multiple linear regression?
Clarification: As discussed in my original question, I am particularly interested in whether the guidance depends on the percentages/proportions being used as an outcome or predictor variable in a linear regression.