Meta-analysis can roughly be divided into aggregate data (AD) meta-analysis and individual participant data (IPD) meta-analysis. AD meta-analysis is the traditional form of meta-analysis and fully focuses on pooling effect sizes that are formulated at the study level, i.e. this analysis represents an analysis of analyses [6]. AD meta-analysis typically combines reported summary statistics from ...

Meta-analysis using individual participant data (IPD) obtains and synthesises the raw, participant-level data from a set of relevant studies. The IPD approach is becoming an increasingly popular tool as an alternative to traditional aggregate data meta-analysis, especially as it avoids reliance on published results and provides an opportunity to investigate individual-level interactions, such a...

OBJECTIVE To assess how common it is to have multiple overlapping meta-analyses of randomized trials published on the same topic. DESIGN Survey of published meta-analyses. DATA SOURCES PubMed. STUDY SELECTION AND METHODS Meta-analyses published in 2010 were identified, and 5% of them were randomly selected. We further selected those that included randomized trials and examined effectivene...

Compositional languages and meta-programming are two approaches of code reusing. Both have its merits and demerits. We distilled the better of these two approaches by coupling disciplined meta-programming features with a compositional language like C++. In this paper we present a meta-programming approach to implement software product lines by designing an Array Product Line to implement differ...

OBJECTIVES Estimation of between-study heterogeneity is problematic in small meta-analyses. Bayesian meta-analysis is beneficial because it allows incorporation of external evidence on heterogeneity. To facilitate this, we provide empirical evidence on the likely heterogeneity between studies in meta-analyses relating to specific research settings. STUDY DESIGN AND SETTING Our analyses includ...

this article presents the application of two algorithms: heuristic big bang-big crunch (hbb-bc) and a heuristic particle swarm ant colony optimization (hpsaco) to discrete optimization of reinforced concrete planar frames subject to combinations of gravity and lateral loads based on aci 318-08 code. the objective function is the total cost of the frame which includes the cost of concrete, formw...

Resource constrained project scheduling problem (RCPSP) is mainly investigated with the objective of either minimizing project makespan or maximizing project net present value. However, when material planning plays a key role in a project, the existing models cannot help determining material ordering plans to minimize material costs. In this paper, the RCPSP incorporated with the material order...

Due to an anticipated increase in air traffic during the next decade, air traffic control in busy airports is one of the main challenges confronting the controllers in the near future. Since the runway is often a bottleneck in an airport system, there is a great interest in optimizing the use of the runway. The most important factors in aircraft landing modeling are time and cost. For this reas...

In this work, we tried to automatically optimize the cost of the concrete segmental lining used as a support system in the case study of Mashhad Urban Railway Line 2 located in NE Iran. Two meta-heuristic optimization methods including particle swarm optimization (PSO) and imperialist competitive algorithm (ICA) were presented. The penalty function was used for unfeasible solutions, and the seg...