Applications of linear mixed model and generalized estimating equation to biological control data

• Main Authors: Chi-Chen Lin, 林其臻
• Other Authors: Hsiu-Yuan Su
• Format: Others
• Language: zh-TW
• Published: 2008
• Online Access: http://ndltd.ncl.edu.tw/handle/99609338700121243103

碩士 === 國立臺灣大學 === 農藝學研究所 === 96 === Longitudinal data can be obtained by observing same object at different time. So the observations are not indepedent with each other.In drug experiment,observations on the reactions of the same patient at different time are not mutually independent. In agriculture,the effect of fertilizers or insecticides can be treated as longitudinal data too, especially for perennial crops. Because of the existence of correlations between observations,it is not appropriate to use general regression analysis or ANOVA.Linear mixed model and generalized estimating equation are two kinds of methods often used in analyzing longitudinal data. Generalized estimating equation divides data into different clusters by their correlations.Then it can be analyzed by general regression analysis ,assuming that the clusters are independent with one another.Linear mixed model is used more often,because the model can be used to analyze the data with fixed and random effect at the same time. The data used in the thesis was provided by Biological Control Laboratory in Department of Plant Protection in National PingTung University of Science & Technology.The main interest is to know the effect of Trichoderma spp. on Rhizoctonia solani with repeated measure data. Chan(2003) analyzed the data by using the method of Biological assay.This thesis analyzes the same data by using linear mixed model and generalized estimating equation.The effect of seven species of Trichoderma spp. is fixed effect and the effect of observations from repeat measurement is random effect.The results are also compared with those obtained by Chan(2003).