Information criteria: AIC, AICc, BIC

Information theoretic approaches view inference as a problem of model selection. The best model is the one that has the least information loss relative to the true model. Information criteria (IC) are estimates of the Kullback Leibler information loss…

Assessing a model: Deviance, Calibration, -2 log likelihood

The performance of a logistic regression model can be described by overall model fit (deviance, Brier score, explained R2), discrimination (C index), calibration (using the intercept and slope of calibration curve, shrinkage) and clinical usefulness.

The beta distribution

The beta distribution represents a probability distribution of probabilities and is the conjugate prior of the binomial distribution in Bayesian analysis…

The binomial distribution

The binomial distribution helps answer common questions such as “a coin is tossed 10 times; what is the probability of getting exactly 6 heads?”