Misunderstandings about <i>Q</i> and ‘Cochran's <i>Q</i> test' in meta‐analysis

Hoaglin, David C.

doi:10.1002/sim.6632

Cited by 233 publications

(156 citation statements)

References 48 publications

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“…However, some of the items on the AMSTAR tool can be misinterpreted. For example, item 9 can be misunderstood to suggest that the choice between a fixed-effect and a random-effects model to combine studies be based on a test of homogeneity, which is misguided [45, 46]. The ISPOR tool has been designed to assess networks with at least one closed loop, which is not always applicable to open-loop networks (i.e., adjusted or anchored indirect comparisons).…”

Section: Discussionmentioning

confidence: 99%

Characteristics and knowledge synthesis approach for 456 network meta-analyses: a scoping review

Zarin

Veroniki

Nincic

et al. 2017

BMC Med

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BackgroundNetwork meta-analysis (NMA) has become a popular method to compare more than two treatments. This scoping review aimed to explore the characteristics and methodological quality of knowledge synthesis approaches underlying the NMA process. We also aimed to assess the statistical methods applied using the Analysis subdomain of the ISPOR checklist.MethodsComprehensive literature searches were conducted in MEDLINE, PubMed, EMBASE, and Cochrane Database of Systematic Reviews from inception until April 14, 2015. References of relevant reviews were scanned. Eligible studies compared at least four different interventions from randomised controlled trials with an appropriate NMA approach. Two reviewers independently performed study selection and data abstraction of included articles. All discrepancies between reviewers were resolved by a third reviewer. Data analysis involved quantitative (frequencies) and qualitative (content analysis) methods. Quality was evaluated using the AMSTAR tool for the conduct of knowledge synthesis and the ISPOR tool for statistical analysis.ResultsAfter screening 3538 citations and 877 full-text papers, 456 NMAs were included. These were published between 1997 and 2015, with 95% published after 2006. Most were conducted in Europe (51%) or North America (31%), and approximately one-third reported public sources of funding. Overall, 84% searched two or more electronic databases, 62% searched for grey literature, 58% performed duplicate study selection and data abstraction (independently), and 62% assessed risk of bias. Seventy-eight (17%) NMAs relied on previously conducted systematic reviews to obtain studies for inclusion in their NMA. Based on the AMSTAR tool, almost half of the NMAs incorporated quality appraisal results to formulate conclusions, 36% assessed publication bias, and 16% reported the source of funding. Based on the ISPOR tool, half of the NMAs did not report if an assessment for consistency was conducted or whether they accounted for inconsistency when present. Only 13% reported heterogeneity assumptions for the random-effects model.ConclusionsThe knowledge synthesis methods and analytical process for NMAs are poorly reported and need improvement.Electronic supplementary materialThe online version of this article (doi:10.1186/s12916-016-0764-6) contains supplementary material, which is available to authorized users.

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Section: Discussionmentioning

confidence: 99%

Characteristics and knowledge synthesis approach for 456 network meta-analyses: a scoping review

Zarin

Veroniki

Nincic

et al. 2017

BMC Med

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“…No matter we use Egger’s or Begg’s test, we had to mention that the power to detect publication bias is low with a small number of included studies56. What’s more, Cochran’s Q and I 2 , which were adopted to detect between-study heterogeneity in our study, can be misleading in meta-analyses if the appropriate reference Q value is not considered57.…”

Section: Discussionmentioning

confidence: 98%

Platelet to lymphocyte ratio in the prediction of adverse outcomes after acute coronary syndrome: a meta-analysis

Liu²,

Tang

2017

Sci Rep

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Recent studies have shown platelet to lymphocyte ratio (PLR) to be a potential inflammatory marker in cardiovascular diseases. We performed a meta-analysis to systematically evaluate the prognostic role of PLR in acute coronary syndrome (ACS). A comprehensive literature search up to May 18, 2016 was conducted from PUBMED, EMBASE and Web of science to identify related studies. The risk ratio (RR) with 95% confidence interval (CI) was extracted or calculated for effect estimates. Totally ten studies involving 8932 patients diagnosed with ACS were included in our research. We demonstrated that patients with higher PLR level had significantly higher risk of in-hospital adverse outcomes (RR = 2.24, 95%CI = 1.81–2.77) and long-term adverse outcomes (RR = 2.32, 95%CI = 1.64–3.28). Sensitivity analyses confirmed the stability of our results. We didn’t detect significant publication bias by Begg’s and Egger’s test (p > 0.05). In conclusion, our meta-analysis revealed that PLR is promising biomarker in predicting worse prognosis in ACS patients. The results should be validated by future large-scale, standard investigations.

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“…DerSimonian and Laird [1] provide the expectation of this statistic and suggested matching this expectation to the observed Q in order to obtain a moments based estimator of τ 2 . Hoaglin [20] clarifies that Cochran used the estimated within-study variances when calculating his statistic; since here we take the within-study variances as fixed and known in analysis, using to indicate Cochran’s heterogeneity statistic suppresses the distinction between the estimated and true within-study variances. This means describing the conventional heterogeneity statistic as Cochran’s heterogeneity statistic is not completely historically accurate.…”

Section: Methodsmentioning

confidence: 99%

Confidence intervals for the between-study variance in random-effects meta-analysis using generalised heterogeneity statistics: should we use unequal tails?

Jackson

Bowden

2016

BMC Med Res Methodol

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BackgroundConfidence intervals for the between study variance are useful in random-effects meta-analyses because they quantify the uncertainty in the corresponding point estimates. Methods for calculating these confidence intervals have been developed that are based on inverting hypothesis tests using generalised heterogeneity statistics. Whilst, under the random effects model, these new methods furnish confidence intervals with the correct coverage, the resulting intervals are usually very wide, making them uninformative.MethodsWe discuss a simple strategy for obtaining 95 % confidence intervals for the between-study variance with a markedly reduced width, whilst retaining the nominal coverage probability. Specifically, we consider the possibility of using methods based on generalised heterogeneity statistics with unequal tail probabilities, where the tail probability used to compute the upper bound is greater than 2.5 %. This idea is assessed using four real examples and a variety of simulation studies. Supporting analytical results are also obtained.ResultsOur results provide evidence that using unequal tail probabilities can result in shorter 95 % confidence intervals for the between-study variance. We also show some further results for a real example that illustrates how shorter confidence intervals for the between-study variance can be useful when performing sensitivity analyses for the average effect, which is usually the parameter of primary interest.ConclusionsWe conclude that using unequal tail probabilities when computing 95 % confidence intervals for the between-study variance, when using methods based on generalised heterogeneity statistics, can result in shorter confidence intervals. We suggest that those who find the case for using unequal tail probabilities convincing should use the ‘1–4 % split’, where greater tail probability is allocated to the upper confidence bound. The ‘width-optimal’ interval that we present deserves further investigation.Electronic supplementary materialThe online version of this article (doi:10.1186/s12874-016-0219-y) contains supplementary material, which is available to authorized users.

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Misunderstandings about Q and ‘Cochran's Q test' in meta‐analysis

Cited by 233 publications

References 48 publications

Characteristics and knowledge synthesis approach for 456 network meta-analyses: a scoping review

Characteristics and knowledge synthesis approach for 456 network meta-analyses: a scoping review

Platelet to lymphocyte ratio in the prediction of adverse outcomes after acute coronary syndrome: a meta-analysis

Confidence intervals for the between-study variance in random-effects meta-analysis using generalised heterogeneity statistics: should we use unequal tails?

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