We did implement this model and test it on data, but not only was fitting it much harder and slower, it also did not yield particularly encouraging results, leading us to omit it from the main text.
c Goodness of fit of our difficulty estimation models Figure 6 shows the log-probability of held-out data under the regression model, by fixing the estimated difficulties (and sometimes also the estimated variance 2 ) to their values obtained from training data, and then finding either MAP estimates or posterior means (by running HMc using STAN) of 29 version (a) is then deficient since it then incorrectly allocates some probability mass to + < 0 and thus < 0 is possible.