392,509 papers found

AIM: : An implicit diagnostic threshold has been thought to be the cause of between-study variation in meta-analyses of diagnostic accuracy studies. Bivariate models have been used to account for implicit diagnostic thresholds. However, little difference in estimates of test performance has been reported between univar…

The objective of this meta-analysis is to assess the impact of LH supplementation in women undergoing in vitro fertilization/ intracytoplasmic sperm injection (IVF/ICSI) with gonadotropin releasing hormone (GnRH) antagonist protocol. No significant difference in outcomes between LH supplementation and r-FSH alone in wo…

Conducting systematic review and meta-analysis (SR/MA) is a standard process for establishing evidences for health technology assessment. Quality assessment of studies included in SR/MA and SR/MA studies should be considered. This article provides recommendations on tools used for assessing the quality of studies inclu…

Network meta-analysis synthesizes direct and indirect evidence in a network of trials that compare multiple interventions and has the potential to rank the competing treatments according to the studied outcome. Despite its usefulness network meta-analysis is often criticized for its complexity and for being accessible…

Meta-analysis of multiple genome-wide association (GWA) studies has become common practice over the past few years. The main advantage of this technique is the maximization of power to detect subtle genetic effects for common traits. Moreover, one can use meta-analysis to probe and identify heterogeneity in the effect…

Although meta-analyses are typically viewed as retrospective activities, they are increasingly being applied prospectively to provide up-to-date evidence on specific research questions. When meta-analyses are updated account should be taken of the possibility of false-positive findings due to repeated significance test…

Studies revealing conflicting results on the role of NAT1 or NAT2 phenotypes on prostate cancer risk led us to perform a meta-analysis to investigate the association of these polymorphisms and prostate cancer risk. The meta-analysis included six studies with NAT1 genotyping (610 prostate cancer cases and 713 controls),…

A key aim of meta-analysis in functional neuroimaging is to quantify the consistency of regional cerebral responses across studies. We derive here a parametric approach to voxel-based meta-analysis, based on spatial statistics. In this method, the value of each voxel in the meta-analysis summary map reflects the propor…

In 2 Monte Carlo studies of fixed- and random-effects meta-analysis for correlations, A. P. Field (2001) ostensibly evaluated Hedges-Olkin-Vevea Fisher-z and Schmidt-Hunter Pearson-r estimators and tests in 120 conditions. Some authors have cited those results as evidence not to meta-analyze Fisher-z correlations, espe…

OBJECTIVE: Risk difference (RD) is often estimated from relative association measures generated by meta-analysis and a particular group's baseline risk. We describe a problematic situation in using this approach. STUDY DESIGN AND SETTING: We encountered a meta-analysis in which a confidence interval (CI) of relative r…

Practical meta-analysis of correlation matrices generally ignores covariances (and hence correlations) between correlation estimates. The authors consider various methods for allowing for covariances, including generalized least squares, maximum marginal likelihood, and Bayesian approaches, illustrated using a 6-dimens…

RATIONALE AND OBJECTIVES: Meta-analyses of diagnostic accuracy studies produce summary estimates of sensitivity and specificity. Cancer staging relies on staging systems and meta-analysis is often performed after dichotomization of the staging results. For each dichotomization, summary estimates of sensitivity and spec…

OBJECTIVE: Interest in evidence-based diagnosis is growing rapidly as diagnostic and screening techniques proliferate. In this article we provide an overview of systematic reviews of diagnostic performance and discuss in detail statistical methods for the most common variant of the problem: meta-analysis of studies in…

Randomized clinical trials provide the most reliable estimates of the benefits and harms of treatments. Limited sample sizes restrict their power to allow informative analyses of secondary outcomes, or patient subgroups. The overall results of trials only apply to the average patient and clinical application ignores th…

Combining the results of individual studies using meta-analysis may be undertaken using either aggregate data (AD) or individual patient data (IPD). In any meta-analysis it is important to consider statistical heterogeneity between studies. Potential sources of heterogeneity can be explored using regression models with…

Meta analysis is a collection of quantitative methods devoted to combine summary information from related but independent studies. Because research reports usually present only data reductions and summary statistics rather than detailed data, the reviewer must often resort to rather crude methods for constructing summa…

Temporal changes in the magnitude of research findings have recently been recognized as a general phenomenon in ecology, and have been attributed to the delayed publication of non-significant results and disconfirming evidence. Here we introduce a method of cumulative meta-analysis which allows detection of both tempor…

Cluster randomization trials have become a very attractive research strategy, particularly for the evaluation of health service interventions. The need to conduct meta-analyses of such trials is also becoming more common. However, as with cluster randomization trials in general, such analyses raise special methodologic…

Clustering functional magnetic resonance imaging (fMRI) time series has emerged in recent years as a possible alternative to parametric modeling approaches. Most of the work so far has been concerned with clustering raw time series. In this contribution we investigate the applicability of a clustering method applied to…

Subgroup analysis is frequently used to investigate heterogeneity in meta-analysis. Subgroup data are not always available, and researchers should record what data were available for each trial. If data were not available, and it is known that the subgroup data were collected, the potential for selective reporting shou…