Difference of measurement data was compared with single factor analysis of variance. After normal transformation, the non-normal distribution data were conducted with statistical disposal.
计量资料差异性比较采用单因素方差分析，非正态分布资料经正态转换后再作统计学处理。
Conclusion the maximum likelihood method based on MCECM algorithm can be used to estimate the parameters of non-linear factor analysis model.
结论基于MCECM算法的极大似然估计方法可用于估计非线性因子分析模型的参数。
Objective To support a reasonable and standard TCM treatment principle for advanced non-small-cell lung cancer (NSCLC) by exploring TCM syndrome features in NSCLC patients with factor analysis.
目的采用因子分析的方法，探讨晚期非小细胞肺癌（NSCLC）中医临床证候特征，为中医药合理规范化地参与晚期肺癌的治疗提供思路。
Objective To support a reasonable and standard TCM treatment principle for advanced non-small-cell lung cancer (NSCLC) by exploring TCM syndrome features in NSCLC patients with factor analysis.
目的采用因子分析的方法，探讨晚期非小细胞肺癌（NSCLC）中医临床证候特征，为中医药合理规范化地参与晚期肺癌的治疗提供思路。
应用推荐