382,842 papers found

There are many questions in the literature that remain unanswered due to the paucity of available subjects or the large sample size needed to detect a difference. A meta-analysis consists of integrating together data from multiple studies into one larger data set in order to increase the subject size and power of a pap…

Meta-analysis has played a key role in psychotherapy research for nearly 40 years. There is now an opportunity for technology to assist with transparent and open meta-analyses. The authors describe an open-access database of effect sizes and a corresponding web application for performing meta-analyses, viewing the data…

Recent research on syllogistic reasoning suggests that the logical status (valid vs. invalid) of even difficult syllogisms can be intuitively detected via differences in conceptual fluency between logically valid and invalid syllogisms when participants are asked to rate how much they like a conclusion following from a…

Meta-analysis is a statistical tool for estimating the mean and variance of underlying population effects from a collection of empirical studies addressing ostensibly the same research question. Meta-analysis has become an increasing popular and valuable tool in psychological research, and major review articles typical…

BACKGROUND: The problem of missing studies in meta-analysis has received much attention. Less attention has been paid to the more serious problem of double counting of evidence. METHODS: Various problems in overstating the precision of results from meta-analyses are described and illustrated with examples, including p…

To introduce the application of Stata software to heterogeneity test in meta-analysis. A data set was set up according to the example in the study, and the corresponding commands of the methods in Stata 9 software were applied to test the example. The methods used were Q-test and I2 statistic attached to the fixed effe…

SUMMARY: Heterogeneity and genome search meta-analysis (HEGESMA) is a comprehensive software for performing genome scan meta-analysis, a quantitative method to identify genetic regions (bins) with consistently increased linkage score across multiple genome scans, and for testing the heterogeneity of the results of each…

The overwhelming increase in the quantity of clinical evidence has led to detachment of the evidence and practice because new evidence can be integrated into clinical practice only after it has been critically appraised and synthesized on the basis of the existing evidence. Because many clinicians lack the skills and t…

Meta-analysis is becoming a key partner of Evidence-Based Medicine. This statistical tool is currently used in most systematic reviews and allows to quantitatively synthesize the results of several studies by a single weighted average whose precision is indicated by the confidence interval. A standardized graphical rep…

This tutorial on advanced statistical methods for meta-analysis can be seen as a sequel to the recent Tutorial in Biostatistics on meta-analysis by Normand, which focused on elementary methods. Within the framework of the general linear mixed model using approximate likelihood, we discuss methods to analyse univariate…

We study recently developed nonparametric methods for estimating the number of missing studies that might exist in a meta-analysis and the effect that these studies might have had on its outcome. These are simple rank-based data augmentation techniques, which formalize the use of funnel plots. We show that they provide…

Systematic reviews and meta-analyses are techniques of data retrieval and analysis which complement traditional narrative reviews. They are widely used in clinical medicine and are finding an increasing role in anatomical pathology. Performing high quality systematic review and meta-analysis requires the accumulation o…

Publication bias is a widespread problem that may seriously distort attempts to estimate the effect under investigation. The literature is reviewed to determine features of the design and execution of both single studies and meta-analyses leading to publication bias, and the role the author, journal editor, and reviewe…

Over the last 20 years, the development of meta-analysis has been aimed at obtaining objective synthesis of the available results on specific research questions. The main achievements of meta-analysis include the application of techniques to perform systematic literature searches and to obtain unbiased selection of stu…

This paper describes the use of a linear mixed-effects regression model as a framework for the meta-analysis of published data. It generalizes the random-effects models used by DerSimonian and Laird (1986, Controlled Clinical Trials 7, 177-188) and Begg and Pilote (1991, Biometrics 47, 899-906), and describes the use o…

Systematic error or bias in a review is hard to avoid when the review is executed without a clearly defined research question and methodology. The methods of systematic review and meta-analysis are designed to address these and other sources of bias with the goal of producing the most valid and precise estimate of effe…

A method is presented for estimating the treatment effect in a meta-analysis when some of the studies are comparative studies, and the rest are noncomparative, historical control studies. A random-effects model is used in which the baseline effect in each study is random, but the treatment effect is constant. With this…

Meta-analysis is a popular statistical technique in biomedical research. In particular, meta-analysis can assist clinicians in determining whether an intervention is effective or which intervention is most effective. Conventional meta-analysis combines aggregated information from multiple published studies and addresse…

Random effects meta-analysis model is an important tool for integrating results from multiple independent studies. However, the standard model is based on the assumption of normal distributions for both random effects and within-study errors, making it susceptible to outlying studies. Although robust modeling using the…

BACKGROUND: Network meta-analysis (NMA) is a widely used method for synthesizing evidence from multiple interventions for a medical condition. However, NMA applications typically ignore the crucial role of drug dosage on intervention effects. Traditional NMAs either consider each intervention dose as an independent nod…