We surveyed 1625 consecutive patients for relevant covariates.
我们调查了1625个连续病例相关指标。
Covariates Zheng Hong cen, not to regret, but paves the way for progress.
郑宏岑，反是不思去后悔，而是为前进铺路。
There were no differences in baseline covariates between groups (P > . 05).
两组间基线指标无差异（P>0.05）。
This method is easy to implement, but it only accommodates discrete covariates .
该方法的缺点是：考虑的协变量只能是分类变量。
It is so called "time-dependent covariates" that the values of covariates change over time.
共变数的值会随著时间而改变时，我们称之为时间相依之共变数。
It is possible that these links are not causal, but rather covariates of the common factor of family.
这是可能的，这些链接不因果关系，而是家庭共同因素协变量。
These covariates included family characteristics and previous problems with thinking, learning and memory.
这些影响因素包括家庭情况和先前思维、学习记忆能力问题。
Discrete-time survival model is appropriate as survival data are discrete, tied and some effects for covariates are added.
当生命数据是离散的、未删失数据含有打结的和有协变量信息时，离散生存分析模型是适当的选择。
Using an intention-to-treat analysis controlling for covariates, data from the 2 prevention groups were analyzed separately.
以意向分析的方式控制共变项，来自这两个预防组的数据分开分析。
This association persisted after adjustment for APACHE II, Multiple Organ Failure score, or the combined covariates cirrhosis, sepsis, oliguria, and mechanical ventilation.
在通过APACHEII，多器官衰竭评分或与硬化，脓毒血症，少尿和机械通气协同变异校正后，这种关联性仍持续存在。
Multivariable linear regression models were then used to assess the joint contributions of the top SNP associations and interactions to ABI after adjustment for covariates.
多变量线性回归模型，然后用来评估联合的贡献顶端的SNP协会和互动，以abi的调整后变。
Results Multilevel models can present the variance covariance metrics of two dependent variables in every levels, and make out the functional expresses of correlation coefficient with covariates.
结果双变量多水平模型可以估计各水平两个变量的方差协方差阵，据此可以计算出相关系数随协变量变化的函数式。
Results Multilevel models can present the variance covariance metrics of two dependent variables in every levels, and make out the functional expresses of correlation coefficient with covariates.
结果双变量多水平模型可以估计各水平两个变量的方差协方差阵，据此可以计算出相关系数随协变量变化的函数式。
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