A functional data approach for analyzing empathic accuracy

Oregon Convention Center 

Empathic accuracy (EA) is the ability to understand the thoughts and emotions of another person, which plays an essential role in shaping social and psychological interactions. Conventional EA analyses often ignore the misalignment of the minds and feelings between people and yield significantly biased results. In this paper, we consider the empathy rating as a function and separate its temporal and vertical variability using the warping-invariant metric-based alignment, which can deal with arbitrary patterns of misalignment. In addition, we propose a penalized functional alignment approach that bounds the temporal alignment of the perceiver's response to the target's emotion to avoid over-alignment. To our knowledge, the proposed approach is among the first to adjust arbitrary patterns of misalignment in the EA study area. We demonstrate the effectiveness of the proposed method using simulated data and two EA data of video and music.

Elastic Shape Analysis

Phase Variability

Functional Mixed Models

Function Alignment 

Mental Health Statistics Section