利用線性混合模式分析生物防治資料

Analyze Biological Control Data Using Linear Mixed Model

蘇秀媛(Hsiu-Yuan Su) ； 林其臻(Chi-Chen Lin) ； 謝鑫能(Hsin-Neng Hsieh)

《Journal of Data Analysis》 6卷2期 (2011/04) Pp. 87-106

https://doi.org/10.6338/JDA.201104_6(2).0005

摘要

縱向資料（longitudinal data）為同一個體，在不同時間下重複測量而得的資料。重複測量資料具有相關性存在，故無法使用一般的迴歸分析或變方分析，需使用其他特別模式進行分析。本文利用木黴菌（Trichoderma spp）可拮抗立枯絲核菌（Rhizoctonia solani）的防治功效，經過一段時間重複觀察，將八種木黴菌取樣和重複測量的觀測值視作隨機效應，木黴菌品種視為固定效應，利用線性混合模式（linear mixed model; LMM）進行分析，比較各品種的木黴菌拮抗三種立枯絲核菌之效能。結果發現，利用LMM在分析每種立枯絲核菌抑制效果最好的木黴菌與生物檢定法（bioassay）分析的結果一致，但LMM在斜率之估計與標準偏差的表現則優於生物檢定法。

關鍵字

縱向資料 ； 線性混合模式 ； 生物防治 ； 真菌生長抑制率

並列摘要

Longitudinal data can be obtained by observing same object at different time. So the observations are not independent with each other. Because of the existence of correlations between observations, it is not appropriate to use general regression analysis or ANOVA. Linear mixed model is a kind of method often used in analyzing longitudinal data. Because linear mixed model can be used to analyze the data with fixed and random effect at the same time. In this study, the main interest is to know the effect of Trichoderma spp. on Rhizoctonia solani with repeated measure data. We use linear mixed model to analyze the effect of Trichoderma spp. on Rhizoctonia solani with repeated measure data. The results are compared with the method of biological assay. We find that the performance of estimation of parameters is better than biological assay.

並列關鍵字

longitudinal data ； linear mixed model ； biological control data ； growth inhibition ratio

參考文獻

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