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首页> 外文期刊>Australian & New Zealand journal of statistics >COMBINING INDIVIDUAL PARTICIPANT DATA AND SUMMARY STATISTICS FROM BOTH CONTINUOUSLY VALUED AND BINARY VARIABLES TO ESTIMATE REGRESSION PARAMETERS
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COMBINING INDIVIDUAL PARTICIPANT DATA AND SUMMARY STATISTICS FROM BOTH CONTINUOUSLY VALUED AND BINARY VARIABLES TO ESTIMATE REGRESSION PARAMETERS

机译：从连续值和二元变量中组合单个参与者数据和摘要统计量，以估计回归参数

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摘要

Recent research has extended standard methods for meta-analysis to more general forms of evidence synthesis, where the aim is to combine different data types or data summaries that contain information about functions of multiple parameters to make inferences about the parameters of interest. We consider one such scenario in which the goal is to make inferences about the association between a primary binary exposure and continuously valued outcome in the context of several confounding exposures, and where the data are available in various different forms: individual participant data (IPD) with repeated measures, sample means that have been aggregated over strata, and binary data generated by thresholding the underlying continuously valued outcome measure. We show that an estimator of the population mean of a continuously valued outcome can be constructed using binary threshold data provided that a separate estimate of the outcome standard deviation is available. The results of a simulation study show that this estimator has negligible bias but is less efficient than the sample mean -the minimum variance ratio is n/2 ≈ 1.57 based on a Taylor series expansion. Combining this estimator with sample means and IPD from different sources (such as a series of published studies) using both linear and probit regression does, however, improve the precision of estimation considerably by incorporating data that would otherwise have been excluded for being in the wrong format. We apply these methods to investigate the association between the G277S mutation in the transferrin gene and serum ferritin (iron) levels separately in pre-and post-menopausal women based on data from three published studies.
机译：最近的研究已将用于荟萃分析的标准方法扩展到证据综合的更一般形式，其目的是结合包含有关多个参数功能的信息的不同数据类型或数据摘要，以推断出感兴趣的参数。我们考虑一种这样的场景，其中的目的是在几个混淆性风险的背景下推断主要的二元风险和持续价值的结果之间的关联，并且可以多种不同的形式获得数据：个人参与者数据（IPD）通过重复测量，样本均值已在各个层级上聚合，并且通过阈值基础连续价值评估结果生成了二进制数据。我们表明，只要结果标准差的单独估计可用，就可以使用二进制阈值数据构造连续值结果的总体平均值的估计量。仿真研究的结果表明，该估计量的偏差可忽略不计，但效率不如样本均值-根据泰勒级数展开式，最小方差比为n / 2≈1.57。但是，使用线性回归和概率回归将此估计量与样本均值和不同来源的IPD（例如一系列已发表的研究）结合使用，确实可以通过合并否则会因错误而被排除的数据而大大提高估计的精度。格式。我们根据来自三项已发表研究的数据，分别研究了绝经前后妇女转铁蛋白基因G277S突变与血清铁蛋白（铁）水平之间的关联。

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