有关统计学方面的东西，高手请帮忙翻译一下

来源：百度知道 编辑：UC知道 时间：2024/05/22 13:05:43
Comparisons were made using analysis of variance for independent samples and x2 tests as appropriate. All hypothesis testing was two-tailed. Cox proportional-hazards regression analysis was used as the appropriate method throughout. Multivariable Cox regression analysis was performed to identify independent predictors of death. Together with BMI, all baseline, demographic, clinical, laboratory, and angiographic variables were entered in a univariable Cox regression analysis. All variables associ- ated with long-term mortality in univariable analysis (P<0.05) were entered into the multivariable model. The linearity assumption was assessed by additionally including the square of the respective covariate in the regression model. For each of the predictor variables, we tested the proportional hazard assumption by including its interaction with time of follow-up into the regression model.

比较了用独立样本和X2适当的试验方差分析。所有假设检验的是双尾。 Cox比例风险回归分析作为整个适当的方法。考克斯多变量回归分析，以确定死亡的独立预测因子。加上体重指数，所有的基线，人口，临床，实验室，和血管造影变量进入一单因素Cox回归分析。所有变量促进协会与长期在单因素分析，短期死亡率性（P“0.05）ated输入了多变量模型。线性假设的评估另外，包括在各自的协变量回归模型平方米。对于每个变量的预测，我们测试，包括其与后续进入回归模型实时交互的比例风险的假设。

比较了采用方差分析、独立样本x2测试。所有的测试都是two-tailed假说。考克斯proportional-hazards回归分析方法作为贯穿始终。多变量分析进行识别的死亡。体重指数(BMI),连同所有基线、人口、临床实验及血管造影的变量是在一个univariable克斯回归分析。所有的变量associ -与长期死亡率在univariable分析(P < 0.05)都进了多变量模型。线性假设是经过另外包括广场的协变量回归模型中。对于每一种预测变量,我们测试了这个比例的风险,包括在假设的随访时进入回归模型