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作 者:张久权[1] 闫慧峰[1] 褚继登 李彩斌 ZHANG Jiu-Quan;YAN Hui-Feng;CHU Ji-Deng;LI Cai-Bin(Tobacco Research Institute,Chinese Academy of Agriculture Sciences/Key Laboratory of Tobacco Biology and Processing,Ministry of Agriculture and Rural Affairs,Qingdao 266101,Shandong,China;Bijie Tobacco Company of Guizhou Province,Bijie 551700,Guizhou,China)
机构地区:[1]中国农业科学院烟草研究所/农业农村部烟草生物学与加工重点实验室,山东青岛266101 [2]贵州省烟草公司毕节市公司,贵州毕节551700
出 处:《作物学报》2021年第2期294-304,共11页Acta Agronomica Sinica
基 金:国家重点研发计划项目(2018YFD201104);四川省烟草公司重点项目(SCYC201702);四川省烟草公司凉山州公司项目(LSYC201601);贵州省烟草公司毕节市公司项目(2018520500240059)资助。
摘 要:重复测量试验对同一受试对象进行多次测量,各时间点数据间存在自相关性,进行方差分析和均值比较时需要进行特殊处理。虽然此方法在农业等研究领域运用十分广泛,但目前有效地相关统计方法鲜见。为了建立操作简单、实用性强、结果可靠的统计分析方法,本研究采用SAS的广义线性混合模型(Generalized Linear Mixed Models,GLIMMIX),以随机区组重复测量试验资料为例,说明了协方差结构筛选、方差分析和均值比较的具体方法。结果表明,用传统的裂区设计、多变量统计等方法会造成资料信息浪费,统计功效降低,缺区无法处理等问题,甚至会导致错误的结论。GLIMMIX能很好地处理自相关问题,功能强大,结果可靠,使用简单,允许缺区,是进行重复测量试验资料方差分析和均值比较的理想方法。目前在国内将其运用到农学类试验数据的统计分析的相关报道鲜见,该文在本领域具有很强的实用性和创新性。Multiple measurements of the same subject are conducted,and there is autocorrelations among the data at each time point.Some special treatment is required for statistical analysis of repeated measure data.Although the repeated measure is widely used in agricultural and other research fields,the relevant and effective statistical methods are rare.In order to establish a simple,easy to use,and reliable statistical method,generalized linear mixed models(GLIMMIX)of SAS was adapted.Selection of covariance structure,variance analysis,and means comparison processes were showed by using RCB data.Traditional split plot and MANOVA methods wasted large amounts of information,reduced the power of the test,and could not handle missing data effectively,even resulting in incorrect conclusions.GLIMMIX was the best choice for variance analysis and means comparison of repeated measure data,because it was easy to use,and had powerful function,high reliability,and ability to handle missing data.At present,there was few relevant report in China,and this method would be very practical and innovative in this field.
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