I have a dataset where I want to assess and compare the performance of different mortality scores (publised scores not model) in burned pediatric population. For a certain score, there is a probability of mortality. I want to test how accurate is the estimated probability (score calculated) with the actual observated event. For this Im using Stata where first I calculate the mortality score and then the probability (from 0 to 1) for each subject. What are the steps for doing an external validation? This is my aproach. For the fitted model, Y= observed mortality, and X1=mortality probability estimated from score. Q1 Is this correct? or shoud I transform the probability into log(odds)? Q2. To assess the utility of the score, I use the AUC ROC from the previous model with just one X variable (probability form score). Is this correct? (c-statistic) Q3. Does it make any sense to try to estimate the calibration of the model, given I only have a summary of it (just the probability, not the model itself)? Q4. If Q3 is affirmative, shoud I use AIC, BIC (other measure of fit) for the comparisson of the different scores or shoud I just compare the AUC ROC (roccomp)?