I have run multiple regression models with factor scores as the DV with several predictor variables (all dichotomous patient characteristics e.g. gender, age). Whilst some predictors and the models are significant, it can only explain less than 2% of the variance at best. We have a large sample size of over 800 participants.
Could this be because... - all the predictors variables are dichotomous - the predictors are not highly correlated with the DV (e.g. ~0.1) - there is not enough variance in the DV
My main questions are why is there such little variance explained, and would it be an issue to report the significant predictors within a paper yet with the overall model only explaining about 2% of the variance?
Thank you