Columnwise Neural Imputation

Columnwise neural imputation (COLNI) uses a neural network with a Compensator layer and a consistent rank logits (CORAL) output layer to impute missing ordinal responses in psychological and educational assessments. Dropout and logit-space nearest-neighbor sampling generate multiple plausible completed datasets to account for imputation uncertainty.