Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

The Impact of Imposing Equality Constraints on Residual Variances Across Classes in Regression Mixture Models

Authors
Choi, JeongwonHong, Sehee
Issue Date
27-1월-2022
Publisher
FRONTIERS MEDIA SA
Keywords
regression mixture model; residual variance; equality constraint; parameter estimation; Monte Carlo simulation study
Citation
FRONTIERS IN PSYCHOLOGY, v.12
Indexed
SSCI
SCOPUS
Journal Title
FRONTIERS IN PSYCHOLOGY
Volume
12
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/138933
DOI
10.3389/fpsyg.2021.736132
ISSN
1664-1078
Abstract
The purpose of this study is to explore the impact of constraining class-specific residual variances to be equal by examining and comparing the parameter estimation of a free model and a constrained model under various conditions. A Monte Carlo simulation study was conducted under several conditions, including the number of predictors, class-specific intercepts, sample size, class-specific regression weights, and class proportion to evaluate the results for parameter estimation of the free model and the restricted model. The free model yielded a more accurate estimation than the restricted model for most of the conditions, but the accuracy of the free model estimation was impacted by the number of predictors, sample size, the disparity in the magnitude of class-specific slopes and intercepts, and class proportion. When equality constraints were imposed in residual variance discrepant conditions, the parameter estimates showed substantial inaccuracy for slopes, intercepts, and residual variances, especially for those in Class 2 (with a lower class-specific slope). When the residual variances were equal between the classes, the restricted model showed better performance under some conditions.
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of Education > Department of Education > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Hong, Se hee photo

Hong, Se hee
사범대학 (교육학과)
Read more

Altmetrics

Total Views & Downloads

BROWSE