And if I reduce the number of observations til 30, it will still be reliable?
I would like to understand which is the threshold criteria, I should follow, in order to trust the prediction. As I understand if I use 30 or 70 observations with 9 variables in the model to distinguish between two groups,
If the Manova test highlight a significant difference (p < 0.01) between the groups in the classification function created. The error estimation by bootstrap and Leave-One-Out is more than ok. And an external sample test set gives good prediction. Could still someone argue that the sample size is not enough, under which criteria?