Impact of analysing continuous outcomes using final values, change scores and analysis of covariance on the performance of meta-analytic methods: a simulation study.
Impact of analysing continuous outcomes using final values, change scores and analysis of covariance on the performance of meta-analytic methods: a simulation study.
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DOI：
10.1002/jrsm.1196
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发表时间：
2016-12
影响因子：
9.8
通讯作者：
Deeks, Jonathan J.
中科院分区：
文献类型：
--
作者：
McKenzie, Joanne E.;Herbison, G. Peter;Deeks, Jonathan J.
当Meta分析从连续结果计算的干预效果时，Meta分析师通常会遇到很少的试验，可能有少量的参与者，以及各种试验分析方法。重要的是要知道这些因素如何影响逆方差固定和DerSimonian和Laird随机效应Meta分析方法的性能。我们使用模拟研究来检查这种性能。通过对最终值、变化评分、ANCOVA或三者的随机混合进行干预效应估计值的Meta分析，得出了汇总干预效应的无偏估计值。当不存在异质性或异质性很低时，试验分析方法对Meta分析性能指标的影响很重要，但随着异质性增加，相关性很小。基于大于标称I类错误率和覆盖率差，当有少量小型试验时，不应使用逆方差固定效应方法。当小型试验较少时，随机效应Meta分析优于固定效应Meta分析。Meta分析估计值需要谨慎解释; I类错误率将大于标称值，置信区间将过窄。在这些情况下使用更有效的试验分析方法可能会产生进一步加剧这些问题的意外后果。版权所有© 2015作者.由John Wiley & Sons，Ltd.出版的研究合成方法© 2015作者。由John Wiley & Sons，Ltd.出版的研究合成方法。
When meta‐analysing intervention effects calculated from continuous outcomes, meta‐analysts often encounter few trials, with potentially a small number of participants, and a variety of trial analytical methods. It is important to know how these factors affect the performance of inverse‐variance fixed and DerSimonian and Laird random effects meta‐analytical methods. We examined this performance using a simulation study. Meta‐analysing estimates of intervention effect from final values, change scores, ANCOVA or a random mix of the three yielded unbiased estimates of pooled intervention effect. The impact of trial analytical method on the meta‐analytic performance measures was important when there was no or little heterogeneity, but was of little relevance as heterogeneity increased. On the basis of larger than nominal type I error rates and poor coverage, the inverse‐variance fixed effect method should not be used when there are few small trials. When there are few small trials, random effects meta‐analysis is preferable to fixed effect meta‐analysis. Meta‐analytic estimates need to be cautiously interpreted; type I error rates will be larger than nominal, and confidence intervals will be too narrow. Use of trial analytical methods that are more efficient in these circumstances may have the unintended consequence of further exacerbating these issues. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd.
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影响因子：
1.9
作者：
Follmann, DA;Proschan, MA
通讯作者：
Proschan, MA
影响因子：
9.8
作者：
McKenzie, Joanne E.;Herbison, G. Peter;Deeks, Jonathan J.
通讯作者：
Deeks, Jonathan J.
影响因子：
7.2
作者：
Hewitt, Catherine E.;Kumaravel, Bharathy;Torgerson, David J.
通讯作者：
Torgerson, David J.
DOI：
10.1016/0197-2456(86)90046-2
发表时间：
1986-09-01
期刊：
CONTROLLED CLINICAL TRIALS
影响因子：
--
作者：
DERSIMONIAN, R;LAIRD, N
通讯作者：
LAIRD, N
影响因子：
7.2
作者：
Deeks, JJ;Macaskill, P;Irwig, L
通讯作者：
Irwig, L