392,317 papers found

Results from single-case studies are being synthesized using three-level models in which repeated observations are nested in participants, which in turn are nested in studies. We examined the performance of these models under conditions in which the errors associated with the repeated observations (the Level-1 errors)…

This commentary critiques the statistical framing and clinical implications of Ramos et al.'s meta-analysis comparing one-anastomosis and Roux-en-Y gastric bypass. While OAGB shows non-inferiority for type 2 diabetes remission under select conditions, its elevated risk of bile reflux and GERD limits its broad applicabi…

We read with great interest the recent meta-analysis by Dai et al. comparing the KangDuo (KD) and da Vinci (DV) robotic systems in radical prostatectomy (RP). Their findings highlight the comparable perioperative outcomes of both systems despite longer operative times with KD. While the study provides valuable insights…

PURPOSE OF REVIEW: Over the past decade, the number of studies published using network meta-analyses (NMAs) has rapidly increased, and there have been continued advancements to further advance this analysis approach. Due to the fast moving and changing landscape in the infancy of NMA methodology, there is a lack of con…

The recent systematic review and meta-analysis by de Oliveria Vacchi, Martha, and Macagnan (2022) on the effect of inspiratory muscle training (IMT) and its association with physical rehabilitation in preoperative anatomic pulmonary resection raises some interesting findings, and the authors should be congratulated for…

Comments on the meta-analysis by G. M. Burlingame et al. (see record 2020-37337-001) on group therapy in schizophrenia. The commenting authors explain why they think that the meta-analysis is seriously flawed and should be recalculated and updated. First, however, they briefly reflect on the role of meta-analyses in co…

The pooled estimate of a recent meta-analysis concluded that rate of reoperation at 1 year was significantly higher in Aortic valve repair (8.82% vs 3.70%) as compared with aortic valve replacement in patients with aortic regurgitation (odds ratio = 2.67, 95% confidence interval [1.08, 3.62], P =&#…

Meta-analysis is a statistical procedure for analyzing the combined data from different studies, and can be a major source of concise up-to-date information. The overall conclusions of a meta-analysis, however, depend heavily on the quality of the meta-analytic process, and an appropriate evaluation of the quality of m…

Network meta-analysis (NMA), also known as multiple treatment comparisons, is commonly used to incorporate direct and indirect evidence comparing treatments. With recent advances in methods and software, Bayesian approaches to NMA have become quite popular and allow models of previously unanticipated complexity. Howeve…

Sequential stopping rules allow hypotheses to be tested using smaller sample sizes than are possible under conventional methods, while controlling the Type I and II error rates. However, the consequences of using such procedures when combining studies in a meta-analysis have rarely been discussed. For a primary study t…

OBJECTIVES: To illustrate the pitfalls of using meta-analysis to combine estimates of effect in trials that are highly varied and have a high potential for bias. METHODS: We used a random-effects meta-analysis to pool the results of 51 sham-controlled acupuncture trials of chronic pain published in English before 2008…

In September 2012 the Acupuncture Trialists' Collaboration published the results of an individual patient data meta-analysis of almost 18 000 patients in high quality randomised trials. The results favoured acupuncture. Although there was little argument about the findings in the scientific press, a controversy played…

This paper investigates the use of likelihood methods for meta-analysis, within the random-effects models framework. We show that likelihood inference relying on first-order approximations, while improving common meta-analysis techniques, can be prone to misleading results. This drawback is very evident in the case of…

Meta-analysis can be a powerful tool for demonstrating the applicability of a concept beyond the context of individual clinical trials and observational studies, including exploration of effects across different subgroups. Meta-analysis avoids Simpson's paradox, in which a consistent effect in constituent trials is rev…

Discovering genes involved in multiple types of cancers is of significant therapeutic importance. We show that collective evidence for such genes can be obtained via a form of meta-analysis that aggregates the results (rankings and p values) from various cancer-specific microarray experiments. This method is illustrate…

BACKGROUND: Understanding of data-reporting methods is imperative for correct interpretation of the medical literature as well as for proper performance of future clinical research. Recent developments in biostatistics have greatly changed the types of statistical analyses used and the minimum quality standards that mu…

Efficacy, which we define as the effect of receiving intervention on health outcomes among a group of subjects, is the quantity of interest for many investigators. In contrast, intent-to-treat analyses in randomized trials and their analogue for observational before-and-after studies compare outcomes between randomizat…

Despite the rapidly growing number of meta-analyses in functional neuroimaging, the field lacks formal mathematical tools for the quantitative and qualitative evaluation of meta-analytic data. We propose to use replicator dynamics in the meta-analysis of functional imaging data to address an important aspect of neuroim…

Meta-analysis has a natural formulation as a Bayesian hierarchical model. The main theoretical difficulty is the construction of a sensible relationship between the parameters of the individual statistical experiments and the meta-parameter. Since that prior information on such a relationship is typically not available…

Meta-analysis is now a standard statistical tool for assessing the overall strength and interesting features of a relationship, on the basis of multiple independent studies. There is, however, recent acknowledgement of the fact that in many applications responses are rarely uniquely determined. Hence there has been som…