| 1. | Likelihood ratio test and power analysis of repeated measures models
重复测量试验模型参数似然比检验及其功效分析 |
| 2. | Objective to explore the statistical methods for repeated measures data
摘要目的探讨临床试验重复测量资料的统计分析方法。 |
| 3. | Not yet , it needs repeated measuring and calculation , and some experience is also very important
还没有。这需要反复的测量和计算，经验也很重要。 |
| 4. | Tests for presuppositions concerning validity of split - plot analysis of variance with repeated measures
医学重复观测数据裂区方差分析的假定条件的检验 |
| 5. | The tests for the presuppositions concerning the validity of univariate analysis of variance with repeated measures
重复观测数据单变量方差分析的前提条件的检验 |
| 6. | The data were analyzed by using percentage , mean , standard deviation , correlation and repeated measure anova statistical methods
所得资料以百分比、平均值、标准差、相关检定、重复量数事后比较、重复量数变异数分析等统计方法处理。 |
| 7. | Methods using an example to illustrate different statistical models ( fixed effects models and mixed models ) in sas procedures for repeated measures data in clinical trials
方法通过实例说明并比较各种固定效应模型和混合模型的优缺点。 |
| 8. | Conclusion modeling the covariance structure is especially important for analysis of repeated measures data because measurements taken close in time are potentially more highly correlated than those taken far apart in time
结论由于在重复测量资料中，同一受试者的不同观测值之间具有相关性特点，故对其指定协方差结构尤其重要。 |
