Editing Meta-analysis (section)

==== Quality effects model ====

Doi and Thalib originally introduced the quality effects model.<ref name="Doi_2008">{{cite journal | vauthors = Doi SA, Thalib L | title = A quality-effects model for meta-analysis | journal = Epidemiology | volume = 19 | issue = 1 | pages = 94–100 | date = January 2008 | pmid = 18090860 | doi = 10.1097/EDE.0b013e31815c24e7 | s2cid = 29723291 | doi-access = free }}</ref> They<ref>{{cite journal | vauthors = Doi SA, Barendregt JJ, Mozurkewich EL | title = Meta-analysis of heterogeneous clinical trials: an empirical example | journal = Contemporary Clinical Trials | volume = 32 | issue = 2 | pages = 288–298 | date = March 2011 | pmid = 21147265 | doi = 10.1016/j.cct.2010.12.006 }}</ref> introduced a new approach to adjustment for inter-study variability by incorporating the contribution of variance due to a relevant component (quality) in addition to the contribution of variance due to random error that is used in any fixed effects meta-analysis model to generate weights for each study. The strength of the quality effects meta-analysis is that it allows available methodological evidence to be used over subjective random effects, and thereby helps to close the damaging gap which has opened up between methodology and statistics in clinical research. To do this a synthetic bias variance is computed based on quality information to adjust inverse variance weights and the quality adjusted weight of the ''i''th study is introduced.<ref name="Doi_2008"/> These adjusted weights are then used in meta-analysis. In other words, if study ''i'' is of good quality and other studies are of poor quality, a proportion of their quality adjusted weights is mathematically redistributed to study ''i'' giving it more weight towards the overall effect size. As studies become increasingly similar in terms of quality, re-distribution becomes progressively less and ceases when all studies are of equal quality (in the case of equal quality, the quality effects model defaults to the IVhet model – see previous section). A recent evaluation of the quality effects model (with some updates) demonstrates that despite the subjectivity of quality assessment, the performance (MSE and true variance under simulation) is superior to that achievable with the random effects model.<ref>{{cite journal | vauthors = Doi SA, Barendregt JJ, Khan S, Thalib L, Williams GM | title = Simulation Comparison of the Quality Effects and Random Effects Methods of Meta-analysis | journal = Epidemiology | volume = 26 | issue = 4 | pages = e42–e44 | date = July 2015 | pmid = 25872162 | doi = 10.1097/EDE.0000000000000289 | doi-access = free }}</ref><ref>{{cite journal | vauthors = Doi SA, Barendregt JJ, Khan S, Thalib L, Williams GM | title = Advances in the meta-analysis of heterogeneous clinical trials II: The quality effects model | journal = Contemporary Clinical Trials | volume = 45 | issue = Pt A | pages = 123–129 | date = November 2015 | pmid = 26003432 | doi = 10.1016/j.cct.2015.05.010 }}</ref> This model thus replaces the untenable interpretations that abound in the literature and a software is available to explore this method further.<ref name="Epigear">{{cite web|url=http://www.epigear.com/ |title=MetaXL software page |publisher=Epigear.com |date=2017-06-03 |access-date=2018-09-18}}</ref>