OK, could I send you my output to get your help. It seems that the best fitting model is the one with 9 factors. However, I have one variable that has a negative residual variance (i.e., LogY1). Does this mean my model is inadmissible? If so, am I at a loss with my data?
A negative residual variance means the model is inadmissible and that you are extracting too many factors. You should have some idea of how many factors to expect based on how the items were created. EFA should be used with items that were carefully created to measure certain dimensions.