A functional data approach for analyzing empathic accuracy
Abstract Number:
2008
Submission Type:
Contributed Abstract
Contributed Abstract Type:
Paper
Participants:
Chul Moon (1), Linh Nghiem (2), Jing Cao (1)
Institutions:
(1) Southern Methodist University, Dallas, Texas, (2) University of Sydney, Sydney, Australia
Co-Author(s):
First Author:
Presenting Author:
Abstract Text:
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.
Keywords:
Elastic Shape Analysis|Phase Variability|Functional Mixed Models|Function Alignment| |
Sponsors:
Mental Health Statistics Section
Tracks:
Latent variable and measurement modeling
Can this be considered for alternate subtype?
No
Are you interested in volunteering to serve as a session chair?
Yes
I have read and understand that JSM participants must abide by the Participant Guidelines.
Yes
I understand that JSM participants must register and pay the appropriate registration fee by June 1, 2024. The registration fee is non-refundable.
I understand
You have unsaved changes.