We review and evaluate selection methods, a prominent class of techniques first proposed by Hedges (1984) that assess and adjust for publication bias in meta-analysis, via an extensive simulation study. Our simulation covers both restrictive settings as well as more realistic settings and proceeds across multiple metrics that assess different aspects of model performance. This evaluation is tim...

When a primary study includes several indicators of the same construct, the usual strategy to meta-analytically integrate the multiple effect sizes is to average them within the study. In this paper, the numerical and conceptual differences among three procedures for averaging dependent effect sizes are shown. The procedures are the simple arithmetic mean, the Hedges and Olkin (1985) procedure,...

We use a case study of a pension plan wishing to hedge the longevity risk in its pension liabilities at a future date. The plan has the choice of using either a customised hedge or an index hedge, with the degree of hedge effectiveness being closely related to the correlation between the value of the hedge and the value of the pension liability. The key contribution of this paper is to show how...

In the hypergraph k-cut problem, the input is a hypergraph, and the goal is to find a smallest subset of hyperedges whose removal ensures that the remaining hypergraph has at least k connected components. This problem is known to be at least as hard as the densest k-subgraph problem when k is part of the input (Chekuri-Li, 2015). We present a randomized polynomial time algorithm to solve the hy...

We propose an algorithm for constraint solving over hedges and contexts built over individual, sequence, function, and context variables and flexible arity symbols, where the admissible bindings of sequence variables and context variables can be constrained to languages represented by regular hedge or regular context expressions. We identify sufficient syntactic restrictions that enable to solv...

We introduce a model for the linguistic hedges ‘very’ and ‘quite’ within the label semantics framework, and combined with the prototype and conceptual spaces theories of concepts. The proposed model emerges naturally from the representational framework we use and as such, has a clear semantic grounding. We give generalisations of these hedge models and show that they can be composed with themse...