两因素方差分析模型确定了随扫描日期调整的良恶性病变差异表达的探针。
A two-way ANOVA model identified probe sets with differential expression in malignant and benign lesions while adjusting for scan dates.
实验数据采用SAS8.2软件包进行单因素方差分析和两因素方差分析。
The data were analysed by one- way ANOVA and two- ways ANOVA using SAS8.2 software package.
利用单因素方差分析检验三组学生之间在策略使用上是否存在显著差异，采用LSD的多重比较进一步指明此种差异存在于哪两组学生之间；
One-way ANOVA was again used to decide significant differences in the use of strategy categories. This was followed by multiple comparisons using LSD to identify where the differences lay.
同时方差分析显示两因素及其配对对浓度有显著影响。
At the same time, analysis of variance showed tile time duration and the pereent and their partnership had the notable infection to the concentration.
多组间的比较采用单因素方差分析，组内两两比较用LSD检验。
One-way ANOVA and LSD were used to analyze all experimental data.
数据输入SPSS17.0统计软件，采用两因素析因设计方差分析进行统计学处理。
Data were inputed into SPSS17.0 statistical software and stastically analyzed by 2factor factorial design ANOVA.
目的：通过混合效应线性模型与单因素方差分析在重复测量资料中的应用比较，旨在说明两方法在处理重复测量资料时的应用特点。
According the characteristics of the bivariate repeated measurement data, using the MIXED procedure of SAS software to fit linear mixed effects model.
目的：通过混合效应线性模型与单因素方差分析在重复测量资料中的应用比较，旨在说明两方法在处理重复测量资料时的应用特点。
According the characteristics of the bivariate repeated measurement data, using the MIXED procedure of SAS software to fit linear mixed effects model.
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