I'm running a binary logistic regression from 5 predictor variables. The outcome variable is match/no match. Although I've run this for four different groups of data with varying distributions on the outcome variable (i.e. Group 1 has match = 500/no match = 1500 and Group 4 has match = 900/no match = 1100, for example) my classification table only predicts 'match'.
Predicted No match Match Actual No Match 0 3048 Match 0 3132 Note: Cut value = .500
This outcome persists regardless of the number of variables included in the model, the proportion of outcome responses, and the cut value. Why might this be happening?