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Jackson, Dan; Turner, Rebecca – Research Synthesis Methods, 2017
One of the reasons for the popularity of meta-analysis is the notion that these analyses will possess more power to detect effects than individual studies. This is inevitably the case under a fixed-effect model. However, the inclusion of the between-study variance in the random-effects model, and the need to estimate this parameter, can have…
Descriptors: Meta Analysis, Databases, Medical Research, Outcomes of Treatment
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Fanshawe, Thomas R.; Shaw, Luke F.; Spence, Graeme T. – Research Synthesis Methods, 2017
Introduction: Previous studies suggest that many systematic reviews contain meta-analyses that display temporal trends, such as the first study's result being more extreme than later studies' or a drift in the pooled estimate. We assessed the extent and characteristics of temporal trends using all Cochrane intervention reports published 2008-2012.…
Descriptors: Meta Analysis, Intervention, Databases, Medical Research
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Béliveau, Audrey; Goring, Sarah; Platt, Robert W.; Gustafson, Paul – Research Synthesis Methods, 2017
In network meta-analysis, the use of fixed baseline treatment effects (a priori independent) in a contrast-based approach is regularly preferred to the use of random baseline treatment effects (a priori dependent). That is because, often, there is not a need to model baseline treatment effects, which carry the risk of model misspecification.…
Descriptors: Risk, Network Analysis, Meta Analysis, Outcomes of Treatment
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Leahy, Joy; O'Leary, Aisling; Afdhal, Nezam; Gray, Emma; Milligan, Scott; Wehmeyer, Malte H.; Walsh, Cathal – Research Synthesis Methods, 2018
The use of individual patient data (IPD) in network meta-analysis (NMA) is becoming increasingly popular. However, as most studies do not report IPD, most NMAs are performed using aggregate data for at least some, if not all, of the studies. We investigate the benefits of including varying proportions of IPD studies in an NMA. Several models have…
Descriptors: Patients, Medical Research, Meta Analysis, Network Analysis