Logo image
Back
Analysis of periodontal data using mixed effects models
Journal article   Open access   Peer reviewed

Analysis of periodontal data using mixed effects models

Young Il Cho and Hae-Young Kim
Journal of periodontal & implant science, v 45(1), pp 2-7
01 Feb 2015
DOI: https://doi.org/10.5051/jpis.2015.45.1.2
PMID: 25722920
Featured in Collection :   UN Sustainable Development Goals @ Drexel
url
https://doi.org/10.5051/jpis.2015.45.1.2View
Published, Version of Record (VoR)CC BY-NC V4.0,  Open

Abstract

Dentistry, Oral Surgery & Medicine Life Sciences & Biomedicine Science & Technology
A fundamental problem in analyzing complex multilevel-structured periodontal data is the violation of independency among the observations, which is an assumption in traditional statistical models (e.g., analysis of variance and ordinary least squares regression). In many cases, aggregation (i.e., mean or sum scores) has been employed to overcome this problem. However, the aggregation approach still exhibits certain limitations, such as a loss of power and detailed information, no cross-level relationship analysis, and the potential for creating an ecological fallacy. In order to handle multilevel-structured data appropriately, mixed effects models have been introduced and employed in dental research using periodontal data. The use of mixed effects models might account for the potential bias due to the violation of the independency assumption as well as provide accurate estimates.

Metrics

12 Record Views
11 citations in Web of Science
9 citations in Scopus

Details

UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#3 Good Health and Well-Being

InCites Highlights

Data related to this publication, from InCites Benchmarking & Analytics tool:

Collaboration types
Domestic collaboration
Web of Science research areas
Dentistry, Oral Surgery & Medicine
Logo image