12/27/2023 0 Comments Random effects meta analysis![]() Finally, the proposed tests are applied to two real data sets to demonstrate their usefulness. We also conduct some simulations to compare the power performance among the proposed tests. Through simulation we show that the proposed tests can control type I error rate. To fill the gap, in this paper we propose some GoF test approaches for meta-analysis to assess if the data are jointly normally distributed, regardless of the type of the mean effects. Last but not least, no GoF test has been developed for meta-analysis in the literature, though some GoF tests have been proposed for generalized linear mixed models 2, 3, 4, 5, 6. Second, many researchers who conduct meta-analysis have limited statistical background and are not aware of this issue and its consequences. First, although many software packages are available, they do not provide GoF tests. Unfortunately, this issue is rarely, if not at all, discussed in practice. The reason we should not ignore this step is that results from an inadequate model may be misleading. Just like in any statistical modeling, the goodness-of-fit test is a critical step to check the model adequacy. Sometimes, results from both FE and RE models were reported 1.Īn important, but usually unanswered, question in meta-analysis is: how the models used fit the data. On the other hand, if this test provides evidence against the homogeneity assumption, the RE model is then used and the results from the RE model are used. If the assumption is not rejected, the FE model is used and the results from FE are reported. First, they perform the Cochran’s test to check the assumption of homogeneity of effects. In practice, many researchers conduct meta-analysis as follows. ![]() This demonstrates that meta-analysis is a popular and useful statistical tool in data analysis.įixed effect (FE) model and random effect (RE) model are the two most commonly used models in meta-analysis, though some less frequently used methods, such as Bayesian meta-analysis and p-value combining approaches, are also available in the literature. For example, when we used “((meta-analy* or metaanaly* or metanaly* or pooled analy* or consorti*) or meta-analysis)” to retrieve researches on meta-analysis from the PubMed database ( ), it returned 65,881 papers published within the most recent five years (as of February 8, 2015). Meta-analysis has been shown to be a very useful tool to combine information it has being intensively used in data analysis 1. On the other hand, however, we are facing the challenge: how to extract useful information from different but related studies. The tremendous amount of data provide us opportunities to answer many scientific questions. Due to technological advancement, the speed of generating large data is increasing. ![]()
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