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Linear regression modeling to compare fluoride release profiles of various restorative materials
被引:14
|作者:
Can-Karabulut, Deniz C.
Batmaz, Ind
Solak, Hikmet
Tastekinl, Mustafa
机构:
[1] Middle E Tech Univ, Arts & Sci Fac, Dept Stat, TR-06531 Ankara, Turkey
[2] Ankara Univ, Fac Sci, Dept Chem, TR-06100 Ankara, Turkey
关键词:
fluoride;
fluoride release;
fluoride ion selective electrode;
fluoride releasing restorative;
materials;
in vitro test;
linear regression modeling;
white noise assumption;
Box-Cox transformation;
D O I:
10.1016/j.dental.2006.06.046
中图分类号:
R78 [口腔科学];
学科分类号:
1003 ;
摘要:
Objectives. The aim of this study was to compare the released fluoride profiles of various restorative materials by using linear regression analysis. Methods. Specimens were prepared using a cylindrical Teflon mold with a height of 2 mm and a radius of 8 mm. After being prepared, specimens were immediately placed into artificial saliva which was replaced at various times during 6 weeks. These released intrinsic fluoride amounts were measured by using an ion selective electrode. Then, data obtained cumulatively were statistically analyzed, and the released profiles were compared. Results. It was observed that the materials released fluoride at different levels of concentration and the largest fluoride release was obtained from the conventional glass ionomer cement. This was followed by resin modified glass ionomer cement, polyacid modified composite resin, and fluoride releasing composite resin, respectively Although the released fluoride amounts of the materials were different, their release profiles were found to be similar in that the release was initially fast and then it became steady as time passed. Significance. The statistical modeling of the release profiles helps to compare the fluoride release behavior of materials and also to predict fluoride release amounts for the future. In literature, for these purposes, separate nonlinear statistical models have extensively been utilized. However, the single linear statistical modeling approach has numerous advantages such as providing estimators having good statistical properties, exact results, precise inference and simplicity in calculation. Therefore, this study was conducted to introduce the use of single linear regression modeling to compare release profiles statistically. (C) 2006 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.
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页码:1057 / 1065
页数:9
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