Coarsening Latent-Class Probabilities: Directional Distortion and Coverage Loss

Outcomes are increasingly regressed on a calibrated probability vector for unobserved class membership, and that vector is often coarsened to a hard label first. Under a constant-coefficient structural mean and conditional calibration, the observed-data problem is a partially linear regression of th...