392,304 papers found

Failure to detect and manage heterogeneity between clinical trials included in meta-analysis may lead to misinterpretation of summary effect estimates. This may ultimately compromise the validity of the results of the meta-analysis. Typically, when heterogeneity between trials is detected, researchers use sensitivity o…

Publication bias threatens the validity of meta-analytic results and leads to overestimation of the effect size in traditional meta-analysis. This particularly applies to meta-analyses that feature small studies, which are ubiquitous in psychology. Here we develop a new method for meta-analysis that deals with publicat…

The quality of tools used in binary classification is evaluated by studies that assess the accuracy of the classification. The empirical evidence is summarized in 2 × 2 contingency tables. These provide the joint frequencies between the true status of a sample and the classification made by the test. The accuracy…

The identification of novel candidate markers is a key challenge in the development of cancer therapies. This can be facilitated by putting accessible and automated approaches analysing the current wealth of 'omic'-scale data in the hands of researchers who are directly addressing biological questions. Data integration…

For the meta-analysis of genome-wide association studies, we propose a new method to adjust for the population stratification and a linear mixed approach that combines family-based and unrelated samples. The proposed approach achieves similar power levels as a standard meta-analysis which combines the different test st…

BACKGROUND: Exposure to endotoxin has been widely investigated as a potential factor for asthma and associated symptoms in children with different results. To clarify a potential relationship, we performed the present meta-analysis to integrate the results of studies examining the association of endotoxin exposure with…

Multi-arm trials meta-analysis is a methodology used in combining evidence based on a synthesis of different types of comparisons from all possible similar studies and to draw inferences about the effectiveness of multiple compared-treatments. Studies with statistically significant results are potentially more likely t…

Normative comparisons are an integral component of neuropsychological test interpretation and provide the basis for an inference of abnormal function and impairment. In order to remedy a deficit of normative standards for a large number of neuropsychology tests, Mitrushina, Boone, Razani, and D'Elia (2005) used the met…

Meta-analysis of heterogeneous clinical trials is currently sub-optimal. This is because there has been no improvement in the method of weighted averaging for such studies since the DL method in 1986. This article presents the argument for the use of situation specific weights to integrate results from such trials. An…

There is sometimes a clear evidence of a strong secular trend in the treatment effect of studies included in a meta-analysis. In such cases, estimating the present-day treatment effect by meta-regression is both reasonable and straightforward. We however consider the more common situation where a secular trend is suspe…

Statistical heterogeneity and small-study effects are 2 major issues affecting the validity of meta-analysis. In this article, we introduce the concept of a limit meta-analysis, which leads to shrunken, empirical Bayes estimates of study effects after allowing for small-study effects. This in turn leads to 3 model-base…

DNA microarray profiles are plagued by the issue of large number of variables but small number of samples and are often notorious for their low signal-to-noise ratio for clinical applications. Therefore, a great need for meta-analysis techniques is emerging to yield more valid and informative results than each experime…

OBJECTIVE: To show how the bivariate random effects meta-analysis model can be used to study the relation between the explanatory variables and the performance of diagnostic tests as characterized by a summary receiver operating characteristic curve (SROCC). STUDY DESIGN AND SETTING: The subject is discussed by means…

Methods for multivariate meta-analysis of genetic association studies are reviewed, summarized and presented in a unified framework. Modifications of standard models are described in detail in order to be applied in genetic association studies. The model based on summary data is uniformly defined for both discrete and…

Recently, meta-analysis has been widely utilized to combine information across comparative clinical studies for evaluating drug efficacy or safety profile. When dealing with rather rare events, a substantial proportion of studies may not have any events of interest. Conventional methods either exclude such studies or a…

In Mendelian randomization a carefully selected gene is used as an instrumental variable in the estimation of the association between a biological phenotype and a disease. A study using Mendelian randomization will have information on an individual's disease status, the genotype and the phenotype. The phenotype must be…

AIMS: It is uncertain whether meta-analyses lead to changes in prescribing practices. We studied trends in the prescribing of glucose-lowering therapy before and after the publication of a meta-analysis suggesting harm from rosiglitazone. METHODS: We examined the prescription records of all residents of Ontario, Canad…

OBJECTIVE: A potential problem with meta-analysis concerns missing studies due to publication bias. This paper focuses on one subtype of publication bias, namely selection bias (studies with unfavorable outcomes tend to be suppressed), wherein the main interest is in determining the proportion of unpublished studies.…

OBJECTIVE: When studies report proportions such as sensitivity or specificity, it is customary to meta-analyze them using the DerSimonian and Laird random effects model. This method approximates the within-study variability of the proportion by a normal distribution, which may lead to bias for several reasons. Alternat…

In meta-analysis of clinical trials, often meta-regression analyses are performed to explain the heterogeneity in treatment effects that usually exist between trials. A popular explanatory variable is the risk observed in the control group, the baseline risk. The relationship between the treatment effect and the baseli…