The use of meta-analysis in economic evaluation

Meta-analysis provides a family of statistical techniques for combining the results of similar studies. This paper examines the meta-analysis of clinical data in economic studies, and points to the issues and considerations that must be addressed when designing and conducting a meta-analysis of clinical data for use in an economic evaluation. We investigate whether the standard approaches employed in the meta-analysis of clinical data are satisfactory to meet the demands of economic evaluation, and assess the meta-analyses contained in a sample of economic evaluations identified from the NHS conomic Evaluation Database. Finally, we provide guidance on the appropriate use of meta-analysis for economic evaluations.economic evaluation, meta-analysis

Detecting Quantum Critical Points using Bipartite Fluctuations

We show that the concept of bipartite fluctuations F provides a very efficient tool to detect quantum phase transitions in strongly correlated systems. Using state of the art numerical techniques complemented with analytical arguments, we investigate paradigmatic examples for both quantum spins and bosons. As compared to the von Neumann entanglement entropy, we observe that F allows to find quantum critical points with a much better accuracy in one dimension. We further demonstrate that F can be successfully applied to the detection of quantum criticality in higher dimensions with no prior knowledge of the universality class of the transition. Promising approaches to experimentally access fluctuations are discussed for quantum antiferromagnets and cold gases.Comment: 5 pages, 6 figures + suppl. material; final version, Phys. Rev. Lett. (in press

General Relation between Entanglement and Fluctuations in One Dimension

In one dimension very general results from conformal field theory and exact calculations for certain quantum spin systems have established universal scaling properties of the entanglement entropy between two parts of a critical system. Using both analytical and numerical methods, we show that if particle number or spin is conserved, fluctuations in a subsystem obey identical scaling as a function of subsystem size, suggesting that fluctuations are a useful quantity for determining the scaling of entanglement, especially in higher dimensions. We investigate the effects of boundaries and subleading corrections for critical spin and bosonic chains.Comment: 4 pages, 2 figures. Minor changes, references added

Improving GDP Measurement: A Forecast Combination Perspective

Two often-divergent U.S. GDP estimates are available, a widely-used expenditure side version, GDPE, and a much less widely-used income-side version, GDPI . We propose and explore a "forecast combination" approach to combining them. We then put the theory to work, producing a superior combined estimate of GDP growth for the U.S., GDPC. We compare GDPC to GDPE and GDPI, with particular attention to behavior over the business cycle. We discuss several variations and extensions.National Income and Product Accounts, Output, Expenditure, Economic Activity, Business Cycle, Recession

Neuroplasticity of the Sensorimotor Cortex during Learning

We will discuss some of the current issues in understanding plasticity in the sensorimotor (SM) cortices on the behavioral, neurophysiological, and synaptic levels. We will focus our paper on reaching and grasping movements in the rat. In addition, we will discuss our preliminary work utilizing inhibition of protein kinase Mζ (PKMζ), which has recently been shown necessary and sufficient for the maintenance of long-term potentiation (LTP) (Ling et al., 2002). With this new knowledge and inhibitors to this system, as well as the ability to overexpress this system, we can start to directly modulate LTP and determine its influence on behavior as well as network level processing dependent at least in part due to this form of LTP. We will also briefly introduce the use of brain machine interface (BMI) paradigms to ask questions about sensorimotor plasticity and discuss current analysis techniques that may help in our understanding of neuroplasticity