PARTIAL LEAST SQUARES (PLS) LATENT VARIABLE MODELLING APPROACH FOR MEASURING DURATION OF ORTHODONTIC TREATMENT
Nur Hanisah Abdul Malek1, Haliza Hasan2 and Maryati Md Dasor3
Faculty of Computer and Mathematical Science,
Universiti Teknologi MARA Cawangan Kelantan
Faculty of Computer and Mathematical Science,
Universiti Teknologi MARA Shah Alam
Faculty of Dentistry, Universiti Teknologi MARA Shah Alam
1This email address is being protected from spambots. You need JavaScript enabled to view it., 2This email address is being protected from spambots. You need JavaScript enabled to view it., 3This email address is being protected from spambots. You need JavaScript enabled to view it.
ABSTRACT
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.
Keywords: Partial Least Squares, Orthodontic treatment, Variable Importance for Projection, Malocclusion, Treatment Planning.
Published On: 16 June 2020
