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A better statistical method of predicting postsurgery soft tissue response in Class II patients

Cited 15 time in Web of Science Cited 15 time in Scopus
Authors
Lee, Ho-Jin; Suh, Hee-Yeon; Lee, Yun-Sik; Lee, Shin-Jae; Donatelli, Richard E.; Dolce, Calogero; Wheeler, Timothy T.
Issue Date
2014-03
Publisher
E.H Angle Education and Research Foundation
Citation
Angle Orthodontist, Vol.84 No.2, pp. 322-328
Keywords
복합학Class II malocclusionSurgical-orthodontic treatmentMultivariate PLS prediction
Abstract
Objective: To propose a better statistical method of predicting postsurgery soft tissue response in Class II patients. Materials and Methods: The subjects comprise 80 patients who had undergone surgical correction of severe Class II malocclusions. Using 228 predictor and 64 soft tissue response variables, we applied two multivariate methods of forming prediction equations, the conventional ordinary least squares (OLS) method and the partial least squares (PLS) method. After fitting the equation, the bias and a mean absolute prediction error were calculated. To evaluate the predictive performance of the prediction equations, a leave-one-out cross-validation method was used. Results: The multivariate PLS method provided a significantly more accurate prediction than the conventional OLS method. Conclusion: The multivariate PLS method was more satisfactory than the OLS method in accurately predicting the soft tissue profile change after surgical correction of severe Class II malocclusions.
ISSN
0003-3219
Language
English
URI
https://hdl.handle.net/10371/92487
DOI
https://doi.org/10.2319/050313-338.1
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College of Dentistry/School of Dentistry (치과대학/치의학대학원)Dept. of Dentistry (치의학과)Journal Papers (저널논문_치의학과)
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