• 利用随机效应模型计算了混合效应的大小。

    Pooled effect sizes were calculated using random effects models.

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  • 利用随机效应模型来估计相对危险度。

    The summary relative risks (RRs) were estimated by the random effects model.

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  • 并使用随机效应统计模式。

    A random effects statistical model was used.

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  • 由两名评论员通过随机效应模型提取数据。

    Two reviewers extracted data, which were aggregated using random-effects models.

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  • 我们采随机效应模式计算平均差(MD)。

    We calculated mean differences (MDs) using a random-effects model.

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  • LM检验证明随机效应模型优于固定效应模型。

    LM test proves the random effect model is superior to the fixed effect model.

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  • 他们测到各组的显著活化,并对组间随机效应做了分析。

    They tested significant activations in each group and differences between the groups with random effect analyses.

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  • 对于每一项可取得的比较项目,我们进行随机效应统合分析。

    Then, for each available comparison, we conducted a random-effects meta-analysis.

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  • 研究了非平衡单向分类随机效应模型中多个异常值的检验问题。

    The detection of multiple outliers in random effects models of the unbalanced one-way classifications is studied in this paper.

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  • 随机效应检查的结果表明,同一地区不同种源的断面积模型相同。

    Meanwhile, the result showed by random effects test demonstrated that basal area models of provenances planted on the same region was of no significant difference.

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  • 若结果有显著差异则报告以随机效应模式呈现,并探讨可能的原因。

    Where significant or apparent heterogeneity was found, results were reported using the random effects model and potential causes of the heterogeneity were sought.

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  • 在采用随机效应模型分析数据后实施预先计划的敏感性和亚组分析。

    Preplanned sensitivity and subgroup analyses were performed after data were analysed with a random-effects model.

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  • 注意随机效应模型没有考虑异质性,在某种意义上,它不是一个议题。

    Note that a random effects model does not 'take account' of the heterogeneity, in the sense that it is no longer an issue.

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  • 共同的相对危险率和95%的可信区间用一种随机效应模型被计算出来。

    Pooled relative risk (RR) and 95% confidence interval (CI) were calculated using a random-effects model.

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  • 当异质性不容易被解释的时候,一个分析方法是将它合并为随机效应模型。

    When there is heterogeneity that cannot readily be explained, one analytical approach is to incorporate it into a random effects model.

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  • 随机效应估计和它的可信区间会提出这样一个问题,“平均效应是什么?”

    The random effects estimate and its confidence interval address the question 'what is the average treatment effect?

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  • 该文研究了非线性随机效应模型,为非线性张度大的模型提供了理论和方法。

    We discussed the nonlinear models with random effects, presented the theory and methods for the models with large nonlinearity.

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  • 方差分量模型的随机效应的协方差为单位阵时《线性模型引论》已进行研究。

    Variance component model of the random effects of covariance matrix unit for the "Linear model introduction" matrix has been studied.

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  • 该文研究了非线性随机效应模型,为非线性张度大的模型提供了理论和方法。

    The least square estimate of covariance matrices in the growth curve model with random effects;

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  • 建立一个有效的分布形式是很困难的,这也是随机效应模型通常被批评的原因。

    It is difficult to establish the validity of any distributional assumption, and this is a common criticism of random effects meta-analyses.

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  • 本文研究了一般的随机效应多元线性模型中线性可估函数的最优线性无偏估计。

    In this paper we investigated optimal linear unbiased estimation of the linear estimable function in general multivariate random effect linear model.

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  • 在考虑公司个体特点的基础上,运用随机效应影响的面板模型进行了敏感性分析。

    Considering the distinguishing feature of diverse companies, sensitive analysis is processed with random-effect panel data model.

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  • 治疗效果采用相对危险度和加权均数差(采用随机效应模型的95%可信区间)概括。

    Treatment effects were summarised as relative risks or weighted mean differences with 95% confidence intervals by using a random effects model.

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  • 当答案不一致时,在任何一个被研究的总体中,随机效应估计也许不能反应真正的效应。

    When the answers do not coincide, the random effects estimate may not reflect the actual effect in any particular population being studied.

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  • 结果通过固定效应与随机效应及对协方差矩阵的估计,使重复测量数据得以合理的分析。

    Results Repeated measurement obtained reasonable results by the fixed and random effects along with efficient estimate of covariance matrix.

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  • 我们应该小心,只有当治疗效应的随机分布的思想被校正的时候,随机效应分析才能被应用。

    Care must be taken that random effects analyses are applied only when the idea of a 'random' distribution of treatment effects can be justified.

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  • 对指数族非线性随机效应模型,本文首次利用Q函数进行统计诊断。主要创新性研究成果如下。

    Q function have been used to study the statistical diagnostics for the exponential family nonlinear models with random effects.

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  • 我们在主要与关键次级结果中,以随机效应模式将资料进行统合分析,并正式地评估其异质性。

    We meta-analysed data using a random-effects model on the primary and key secondary outcomes and formally assessed heterogeneity.

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  • 首先刻画了非线性随机效应模型的异方差类型,进而研究了非线性随机效应模型的异方差检验;

    We first develop the tests for varying dispersion in two special generalized nonlinear models of longitudinal data: (1) logistic nonlinear models in binomial data;

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  • 随机效应分析被用作比较体现出异质性的试验,而固定效应方向则用来比较体现出同质性的试验。

    Random-effects analysis was used for comparing trials showing heterogeneity, and fixed-effects analysis was used for comparing trials showing homogeneity.

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