Meta分析的拟合优度检验。
Goodness-of-fit test for meta-analysis.
作者信息
Chen Zhongxue, Zhang Guoyi, Li Jing
机构信息
Department of Epidemiology and Biostatistics, School of Public Health, Indiana University Bloomington, 1025 E. 7th street, Bloomington, IN 47405, USA.
Department of Mathematics and Statistics, University of New Mexico, Albuquerque, NM 87131, USA.
出版信息
Sci Rep. 2015 Nov 23;5:16983. doi: 10.1038/srep16983.
Meta-analysis is a very useful tool to combine information from different sources. Fixed effect and random effect models are widely used in meta-analysis. Despite their popularity, they may give us misleading results if the models don't fit the data but are blindly used. Therefore, like any statistical analysis, checking the model fitting is an important step. However, in practice, the goodness-of-fit in meta-analysis is rarely discussed. In this paper, we propose some tests to check the goodness-of-fit for the fixed and random effect models with assumption of normal distributions in meta-analysis. Through simulation study, we show that the proposed tests control type I error rate very well. To demonstrate the usefulness of the proposed tests, we also apply them to some real data sets. Our study shows that the proposed tests are useful tools in checking the goodness-of-fit of the normal models used in meta-analysis.
荟萃分析是整合来自不同来源信息的非常有用的工具。固定效应模型和随机效应模型在荟萃分析中被广泛使用。尽管它们很受欢迎，但如果模型不适合数据却被盲目使用，可能会给我们带来误导性结果。因此，与任何统计分析一样，检查模型拟合是重要的一步。然而，在实际中，很少讨论荟萃分析中的拟合优度。在本文中，我们提出了一些检验方法，用于在荟萃分析中假设正态分布的情况下检查固定效应模型和随机效应模型的拟合优度。通过模拟研究，我们表明所提出的检验能很好地控制第一类错误率。为了证明所提出检验的有用性，我们还将它们应用于一些实际数据集。我们的研究表明，所提出的检验是检查荟萃分析中使用的正态模型拟合优度的有用工具。
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