Open mankoff opened 2 years ago
The results of figure 2 derive directly from the definition of predicted (P) and observed (O) data. In particular, P=O+err, while P has no error. I am not familiar with ecological modelling, but I would adopt the opposite definition, i.e., O=P+err. That is, the model is affected by some form of uncertainty, while the observations are "correct". Using this convention to plot the data implies that the correct way is PO (predicted y, observed x). In the end, I think that the choice between PO and OP depends on what are you presenting and what information you intend to communicate
Thanks for commenting here - I agree, it is often reasonable to assume model has error and observations are correct. Depends on the situation.
In the case of "validating my new product against existing 'standards'", maybe assuming that the new product has errors is reasonable (although, of course, historical standards also have errors).
Although, methods exist to deal with errors and uncertainty in both the dependent and independent variable. Seems like those are the better methods to use.
PO (Predicted x, Observed y) is incorrect, and you should plot OP (Observed y, Predicted x), according to https://doi.org/10.1016/j.ecolmodel.2008.05.006