392,419 papers found

Network meta-analysis is the established method to pool evidence from multiple clinical trials and make direct and indirect comparisons between different treatments. To ensure its validity, one of the major assumptions requiring examination is that the different sources of information are consistent, which is to say th…

Synthesis of medical literature to determine the best treatment for a given problem is challenging, particularly when multiple options exist. Network meta-analysis (NMA) allows the comparison of different treatment approaches in a single, systematic review including treatments that have never been compared head-to-head…

BACKGROUND: This meta-analysis was to systematically investigate the effect of breastfeeding on metabolic-related outcomes in women with previous gestational diabetes mellitus (GDM). METHODS: We will search the online databases of Relevant studies were searched in Pubmed, Embase, Cochrane Library, Web of Science. Rela…

BACKGROUND: Shexiang Baoxin Pills (SBP) is widely used for the treatment of unstable angina pectoris (UAP) in China. However, the clinical evidence on the efficacy of SBP for the treatment of UAP is not well concluded. METHODS: Seven electronic databases will be searched for eligible studies: MEDLINE, EMBASE, The Coch…

Meta-analysis of microarray studies to produce an overall gene list is relatively straightforward when complete data are available. When some studies lack information-providing only a ranked list of genes, for example-it is common to reduce all studies to ranked lists prior to combining them. Since this entails a loss…

Multivariate meta-analysis is becoming more commonly used. Methods for fitting the multivariate random effects model include maximum likelihood, restricted maximum likelihood, Bayesian estimation and multivariate generalisations of the standard univariate method of moments. Here, we provide a new multivariate method of…

BACKGROUND: Meta-analysis is a statistical method for combining the results of primary studies. It is often used in systematic reviews and is increasingly a method and topic that appears in student dissertations. MetaLight is a freely available software application that runs simple meta-analyses and contains specific f…

The Copas parametric model is aimed at exploring the potential impact of publication bias via sensitivity analysis, by making assumptions regarding the probability of publication of individual studies related to the standard error of their effect sizes. Reviewers often have prior assumptions about the extent of selecti…

SUMMARY: phyloMeta is an easy to use console program for integrating phylogenetic information into meta-analysis. It is designed to help ecologists, evolutionary biologists and conservation biologists analyze effect size data extracted from published studies in a comparative phylogenetic context. This software estimate…

Meta-analysis is becoming a principal tool for research synthesis and for the identification and justification of evidence based practices. A fundamental assumption in meta-analysis is that effect sizes based upon different measures are comparable. Recent work has challenged this assumption in the case of the standardi…

The inverse normal and Fisher's methods are two common approaches for combining P-values. Whitlock demonstrated that a weighted version of the inverse normal method, or 'weighted Z-test', is superior to Fisher's method for combining P-values for one-sided T-tests. The problem with Fisher's method is that it does not ta…

This article discusses statistical approaches to the validation of surrogate biomarkers and endpoints. One approach that has been successfully used in oncology consists of estimating associations at two levels: the association between the surrogate and the clinical endpoint, called the individual-level association, and…

BACKGROUND: Publicly available datasets of microarray gene expression signals represent an unprecedented opportunity for extracting genomic relevant information and validating biological hypotheses. However, the exploitation of this exceptionally rich mine of information is still hampered by the lack of appropriate com…

The authors describe the relative benefits of conducting meta-analyses with (a) individual participant data (IPD) gathered from the constituent studies and (b) aggregated data (AD), or the group-level statistics (in particular, effect sizes) that appear in reports of a study's results. Given that both IPD and AD are eq…

Analysis of a randomized trial with missing outcome data involves untestable assumptions, such as the missing at random (MAR) assumption. Estimated treatment effects are potentially biased if these assumptions are wrong. We quantify the degree of departure from the MAR assumption by the informative missingness odds rat…

In many ways, adjustment for publication bias in meta-analysis parallels adjustment for ascertainment bias in genetic studies. We investigate a previously published simulation-based method for dealing with complex ascertainment bias and show that it can be modified for use in meta-analysis when publication bias is susp…

We use a hierarchical model for a meta-analysis that combines information from autopsy studies of adenoma prevalence and counts. The studies we included reported findings using a variety of adenoma prevalence groupings and age categories. We use a non-homogeneous Poisson model for multinomial bin probabilities. The Poi…

Although population-based molecular association studies are becoming increasingly popular, methodology for the meta-analysis of these studies has been neglected, particularly with regard to two issues: testing Hardy-Weinberg equilibrium (HWE), and pooling results in a manner that reflects a biological model of gene eff…

Although use of the standardized mean difference in meta-analysis is appealing for several reasons, there are some drawbacks. In this article, we focus on the following problem: that a precision-weighted mean of the observed effect sizes results in a biased estimate of the mean standardized mean difference. This bias i…