Guidelines for Meta-analyses and Systematic Reviews in Urology.

Our guideline comprises points addressing the conduct and interpretation of systematic reviews and meta-analyses in urology. Application of the guideline would lead to a more considered interpretation of a smaller number of systematic reviews and meta-analyses, and could thus help in translating evidence into better decision-making for doctors and patients.

Advances in meta-analysis: A unifying modelling framework with measurement error correction.

In psychological studies, multivariate outcomes measured on the same individuals are often encountered. Effects originating from these outcomes are consequently dependent. Multivariate meta-analysis examines the relationships of multivariate outcomes by estimating the mean effects and their variance-covariance matrices from series of primary studies.

A group-specific prior distribution for effect-size heterogeneity in meta-analysis.

While both methodological and applied work on Bayesian meta-analysis have flourished, Bayesian modeling of differences between groups of studies remains scarce in meta-analyses in psychology, education, and the social sciences. On rare occasions when Bayesian approaches have been used, non-informative prior distributions have been chosen. However, more informative prior distributions have recently garnered popularity.

Quasi-experimental study designs series-paper 10: synthesizing evidence for effects collected from quasi-experimental studies presents surmountable challenges.

Objective: To outline issues of importance to analytic approaches to the synthesis of quasi-experiments (QEs) and to provide a statistical model for use in analysis.

Study Design And Setting: We drew on studies of statistics, epidemiology, and social-science methodology to outline methods for synthesis of QE studies. The design and conduct of QEs, effect sizes from QEs, and moderator variables for the analysis of those effect sizes were discussed.

Quasi-experimental study designs series-paper 9: collecting data from quasi-experimental studies.

Objective: To identify variables that must be coded when synthesizing primary studies that use quasi-experimental designs.

Study Design And Setting: All quasi-experimental (QE) designs.

Results: When designing a systematic review of QE studies, potential sources of heterogeneity-both theory-based and methodological-must be identified.

Quiet Eye and Performance in Sport: A Meta-Analysis.

Research linking the "quiet eye" (QE) period to subsequent performance has not been systematically synthesized. In this paper we review the literature on the link between the two through nonintervention (Synthesis 1) and intervention (Synthesis 2) studies. In the first synthesis, 27 studies with 38 effect sizes resulted in a large mean effect (d = 1.

The impact of multiple endpoint dependency on Q and I(2) in meta-analysis.

A common assumption in meta-analysis is that effect sizes are independent. When correlated effect sizes are analyzed using traditional univariate techniques, this assumption is violated. This research assesses the impact of dependence arising from treatment-control studies with multiple endpoints on homogeneity measures Q and I(2) in scenarios using the unbiased standardized-mean-difference effect size.

Model-driven meta-analyses for informing health care: a diabetes meta-analysis as an exemplar.

A relatively novel type of meta-analysis, a model-driven meta-analysis, involves the quantitative synthesis of descriptive, correlational data and is useful for identifying key predictors of health outcomes and informing clinical guidelines. Few such meta-analyses have been conducted and thus, large bodies of research remain unsynthesized and uninterpreted for application in health care. We describe the unique challenges of conducting a model-driven meta-analysis, focusing primarily on issues related to locating a sample of published and unpublished primary studies, extracting and verifying descriptive and correlational data, and conducting analyses.

Synthesizing regression results: a factored likelihood method.

Regression methods are widely used by researchers in many fields, yet methods for synthesizing regression results are scarce. This study proposes using a factored likelihood method, originally developed to handle missing data, to appropriately synthesize regression models involving different predictors. This method uses the correlations reported in the regression studies to calculate synthesized standardized slopes.

The Degree of Dependence Between Multiple-Treatment Effect Sizes.

We examined the degree of dependence between standardized-mean-difference effect sizes in multiple-treatment studies in meta-analysis in terms of the correlation formula provided by Gleser and Olkin (1994) . To explore the impact of group size and the values of the true multiple-treatment effect sizes, we simplified the formula for the correlation in terms of the ratio of group sizes and under conditions of equality of sample and effect sizes. The results showed that the group-size ratio affects the correlation between effects much more than do the values of the effect sizes.

A meta-analysis of direct and mediating effects of community coalitions that implemented science-based substance abuse prevention interventions.

This article reports results of a meta-analysis of the effects of a set of community coalitions that implemented science-based substance use prevention interventions as part of a State Incentive Grant (SIG) in Kentucky. The analysis included assessment of direct effects on prevalence of substance use among adolescents as well as assessment of what "risk" and "protective" factors mediated the coalition effects. In addition, we tested whether multiple science-based prevention interventions enhanced the effects of coalitions on youth substance use.

The meaning and suitability of various effect sizes for structured Rater x Ratee designs.

Four types of analysis are commonly applied to data from structured Rater x Ratee designs. These types are characterized by the unit of analysis, which is either raters or ratees, and by the design used, which is either between-units or within-unit design. The 4 types of analysis are quite different, and therefore they give rise to effect sizes that differ in their substantive interpretations.

Physical activity and psychological well-being in advanced age: a meta-analysis of intervention studies.

A meta-analysis examined data from 36 studies linking physical activity to well-being in older adults without clinical disorders. The weighted mean-change effect size for treatment groups (d(C). = 0.