Combining studies using effect sizes and quality scores:: Application to bone loss in postmenopausal women
Combining studies using effect sizes and quality scores:: Application to bone loss in postmenopausal women
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DOI：
10.1016/s0895-4356(98)00073-0
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发表时间：
1998-10-01
影响因子：
7.2
通讯作者：
Bravo, G
中科院分区：
文献类型：
--
作者：
Bérard, A;Bravo, G
本文提出了一个随机效应模型，该模型使用效应量（ES）和质量分数来整合调查结果。一个实证的例子是从一个荟萃分析的有效性的身体活动在预防骨质流失的健康绝经后妇女的数据。进行Medline检索以查找1966年1月至1996年5月期间以法语或英语发表的相关研究。三位独立的评审员从研究中提取数据。根据Hedges和Olkin的方法计算效应量。采用改良版的查尔默斯量表计算质量评分。使用DerSimonian和Laird方法结合质量评分来估计总体效应量。在合并研究时，质量评分和方差倒数作为权重。体力活动对健康绝经后妇女脊柱骨密度损失影响的总体估计值和标准误（SE）为ES总体= 0.4263（1.1361）。当与其他荟萃分析方法（如固定效应模型和没有质量评分（DL）的DerSimonian和Laird模型）相比时，新模型生成了可比较的估计值（固定效应模型的ES总体（SE）= 1.2724（0.0139），DL ES总体（SE）= 0.3958（1.2370））。由于研究之间存在异质性，随机效应模型比固定效应模型更合适。然而，正如预期的那样，它导致了更宽的置信区间。经验表明，使用质量分数的模型比单独的DL模型产生更窄的置信区间。在荟萃分析中纳入协变量，如质量评分，可以量化研究之间的差异。(C)1998年爱思唯尔科学公司
This article presents a random effects model that uses effect sizes (ES) and quality scores to integrate results from investigations. An empirical example is given with data obtained from a meta-analysis on the effectiveness of physical activity in the prevention of bone loss in healthy postmenopausal women. A Medline search was performed to locate relevant studies published in French or English between January 1966 and May 1996. Three independent reviewers extracted data from studies. Effect sizes were calculated according to the method of Hedges and Olkin. A modified version of Chalmers' scale was utilized to calculate quality scores. DerSimonian and Laird's method with incorporation of the quality scores was used to estimate the overall effect size. Quality scores and the inverse of the variances were included as weights when combining studies. The overall estimate and standard error (SE) of the effect of physical activity on spinal bone mineral density loss in healthy postmenopausal women was ESoverall = 0.4263 (1.1361). When compared to other meta-analysis methods such as the fixed effects model and the model of DerSimonian and Laird without the quality score (DL), the new model generated comparable estimators (fixed effects model's ESoverall (SE) = 1.2724 (0.0139), DLs ESoverall (SE) = 0.3958 (1.2370)). Due to the heterogeneity that existed between studies, a random effects model was more appropriate then a fixed effects model. However, it resulted in wider confidence intervals, as expected. it was shown empirically that the model using quality scores generated narrower confidence intervals than the model of DL alone. The inclusion of covariates such as quality scores in meta-analyses permits the quantification of the variation between studies. (C) 1998 Elsevier Science Inc.