現今醫學運用精油於治療病症之相關文獻非常豐富，但多數臨床治療僅依經驗法則，毫無系統性，進而浪費成本於治療上，然而這種現象，其主要原因是沒有一套經過精省設計的科學統計方法。
有鑑於此，本文以兩階段建模之實驗設計法，將精油推拿治療應用於類風溼關節炎、預後性腦中風與單純性肥胖症三種常見病症上。以往在精油推拿治療上，常只以精油之主要功效來判斷其療效，而忽略了不同精油間之交互作用效應佔有一定影響力，間接影響了整體療效。因此本文旨在建構一套嚴謹實用的實驗設計法則，並將之應用於常見之病症治療上。
本研究以精油與病症建立出一精省模型，此模型可用以預測病症療效，進而節省成本。本文實際對病患進行採樣篩選並量取數據，再進行效應、變異與顯著等分析找出顯著因子與主要效應與交互效應，並透過分塊設計以消彌男女個體間之誤差，提升精確度，完成最適精省回歸模型之建構。本研究最後運用逆Yates作精油選取之設計，藉由精油貢獻度與回歸模型之關係，將最適精省回歸模型進行細部調控、設計改良，將原預測目標值在同樣限定條件下，作精油濃度配適較佳之新組合。

The use of essential oils to treat diseases in modern medical application is very rich in literature. However, most of the clinical treatments are just accordance with the rule of thumb, without systematic. Sometimes the treatment effect is disappointing, resulted in a waste costs in treatment. The main reason is that we have no a set of scientific and statistical methods designed after provincial downsizing.
In view of the emerging needs, this thesis proposes a two-stage experimental design method for the treatment of disease by essential oils via chiropractic approach with reference to three commonly encounter human diseases including rheumatoid arthritis, cerebral vascular accident and obesity. In the past, we often determine its efficacy mainly based upon main effect of the essential oils but ignoring the effect of interactions between different essential oils. The interaction indirectly affects the overall efficacy. This thesis is devoted to construct sets of rigorous experimental and practical design rules for possible modeling and applications for commonly human diseases.
In this study, the main objective is to construct a fine provincial model for the essential oils for curing certain specified diseases. This model can be used to predict disease efficacy, and thus can be utilized to save costs. The employment of error analysis, variance analysis and significant analysis make possible the identification of significant parameters and the interactive terms. In order to improve modeling accuracy, block design is employed to dispelling the error between the male and female individuals, and the construction of an accurate and economic regression model for commonly encounter human diseases is accomplished. The results are applied for further redesign and are shown to be effective and accurate.In this study, we use the method of Inverse Yates for the design of essential oils selected by the refined contribution of the essential oils. The provincial regression model can be detailed to modify and to converted into the original forecast target value for the same conditions to come up with better essential oils combination.

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