Partial least squares (PLS) latent variable modelling approach for measuring duration of orthodontic treatment / Nur Hanisah Abdul Malek, Haliza Hasan and Maryati Md Dasor

In today's society, the quest for aesthetic perfection is no longer just an aspiration of the young. As a result, there is an increasing number of adult patients who seek for orthodontic treatment to improve not only the function but the appearance of their teeth as well. Patients who are going...

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Main Authors: Abdul Malek, Nur Hanisah, Hasan, Haliza, Md Dasor, Maryati
Format: Article
Language:English
Published: Universiti Teknologi MARA 2020
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Online Access:http://ir.uitm.edu.my/id/eprint/48083/1/48083.pdf
http://ir.uitm.edu.my/id/eprint/48083/
https://mjoc.uitm.edu.my
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spelling my.uitm.ir.480832021-06-24T09:33:14Z http://ir.uitm.edu.my/id/eprint/48083/ Partial least squares (PLS) latent variable modelling approach for measuring duration of orthodontic treatment / Nur Hanisah Abdul Malek, Haliza Hasan and Maryati Md Dasor Abdul Malek, Nur Hanisah Hasan, Haliza Md Dasor, Maryati RK Dentistry Orthodontics In today's society, the quest for aesthetic perfection is no longer just an aspiration of the young. As a result, there is an increasing number of adult patients who seek for orthodontic treatment to improve not only the function but the appearance of their teeth as well. Patients who are going to wear braces will be curious on how long the orthodontic treatment will take and those who complete treatment on time may be more satisfied. Therefore, this retrospective study aims to model the factors that affect the duration of orthodontic treatment using Partial Least Squares Regression. Demographic profile, patient's severity of malocclusion, treatment planning and patient compliance data are collected from patient's folders who have completed orthodontic treatment. The result from Partial Least Squares (PLS) regression indicates that twelve variables which are patient's age, patient's gender, proposed treatment planning, seven malocclusion characteristics, clinician experience and oral hygiene condition significantly contribute to the treatment duration. This study also demonstrates the application of Variable Importance for Projection (VIP) to select significant predictor variables. The final PLS model with one extracted factor explains 89.96% of the variation in the duration of orthodontic treatment. Universiti Teknologi MARA 2020-06 Article PeerReviewed text en http://ir.uitm.edu.my/id/eprint/48083/1/48083.pdf ID48083 Abdul Malek, Nur Hanisah and Hasan, Haliza and Md Dasor, Maryati (2020) Partial least squares (PLS) latent variable modelling approach for measuring duration of orthodontic treatment / Nur Hanisah Abdul Malek, Haliza Hasan and Maryati Md Dasor. Malaysian Journal of Computing (MJoC), 5 (1). pp. 469-479. ISSN (eISSN): 2600-8238 https://mjoc.uitm.edu.my
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic RK Dentistry
Orthodontics
spellingShingle RK Dentistry
Orthodontics
Abdul Malek, Nur Hanisah
Hasan, Haliza
Md Dasor, Maryati
Partial least squares (PLS) latent variable modelling approach for measuring duration of orthodontic treatment / Nur Hanisah Abdul Malek, Haliza Hasan and Maryati Md Dasor
description In today's society, the quest for aesthetic perfection is no longer just an aspiration of the young. As a result, there is an increasing number of adult patients who seek for orthodontic treatment to improve not only the function but the appearance of their teeth as well. Patients who are going to wear braces will be curious on how long the orthodontic treatment will take and those who complete treatment on time may be more satisfied. Therefore, this retrospective study aims to model the factors that affect the duration of orthodontic treatment using Partial Least Squares Regression. Demographic profile, patient's severity of malocclusion, treatment planning and patient compliance data are collected from patient's folders who have completed orthodontic treatment. The result from Partial Least Squares (PLS) regression indicates that twelve variables which are patient's age, patient's gender, proposed treatment planning, seven malocclusion characteristics, clinician experience and oral hygiene condition significantly contribute to the treatment duration. This study also demonstrates the application of Variable Importance for Projection (VIP) to select significant predictor variables. The final PLS model with one extracted factor explains 89.96% of the variation in the duration of orthodontic treatment.
format Article
author Abdul Malek, Nur Hanisah
Hasan, Haliza
Md Dasor, Maryati
author_facet Abdul Malek, Nur Hanisah
Hasan, Haliza
Md Dasor, Maryati
author_sort Abdul Malek, Nur Hanisah
title Partial least squares (PLS) latent variable modelling approach for measuring duration of orthodontic treatment / Nur Hanisah Abdul Malek, Haliza Hasan and Maryati Md Dasor
title_short Partial least squares (PLS) latent variable modelling approach for measuring duration of orthodontic treatment / Nur Hanisah Abdul Malek, Haliza Hasan and Maryati Md Dasor
title_full Partial least squares (PLS) latent variable modelling approach for measuring duration of orthodontic treatment / Nur Hanisah Abdul Malek, Haliza Hasan and Maryati Md Dasor
title_fullStr Partial least squares (PLS) latent variable modelling approach for measuring duration of orthodontic treatment / Nur Hanisah Abdul Malek, Haliza Hasan and Maryati Md Dasor
title_full_unstemmed Partial least squares (PLS) latent variable modelling approach for measuring duration of orthodontic treatment / Nur Hanisah Abdul Malek, Haliza Hasan and Maryati Md Dasor
title_sort partial least squares (pls) latent variable modelling approach for measuring duration of orthodontic treatment / nur hanisah abdul malek, haliza hasan and maryati md dasor
publisher Universiti Teknologi MARA
publishDate 2020
url http://ir.uitm.edu.my/id/eprint/48083/1/48083.pdf
http://ir.uitm.edu.my/id/eprint/48083/
https://mjoc.uitm.edu.my
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score 13.214268