GLM output for deviance and loglikelihood
On Apr 21, 2011, at 05:14 , Juliet Hannah wrote:
As you mentioned, the deviance does not always reduce to: D = -2(loglikelihood(model)) It does for ungrouped data, such as for binary logistic regression.
To be precise, it only happens when the log likelihood of the saturated model is 0, which for discrete models implies that the probability of the observed data under the saturated model is 1. Binary data is pretty much the _only_ case where this is true (because individual fitted probabilities become either zero or one).
Peter Dalgaard Center for Statistics, Copenhagen Business School Solbjerg Plads 3, 2000 Frederiksberg, Denmark Phone: (+45)38153501 Email: pd.mes at cbs.dk Priv: PDalgd at gmail.com