Modelling mortality rates using GEE models

Generalised estimating equation (GEE) models are extensions of generalised linear models by relaxing the assumption of independence. These models are appropriate to analyze correlated longitudinal responses which follow any distribution that is a member of the exponential family. This model is used to relate daily mortality rate of Maltese adults aged 65 years and over with a number of predictors, including apparent temperature, season and year. To accommodate the right skewed mortality rate distribution a Gamma distribution is assumed. An identity link function is used for ease of interpretating the parameter estimates. An autoregressive correlation structure of order 1 is used since correlations decrease as distance between observations increases. The study shows that mortality rate and temperature are related by a quadratic function. Moreover, the GEE model identifies a number of significant main and interaction effects which shed light on the effect of weather predictors on daily mortality rates.peer-reviewe

Study of excited nucleon states at EBAC: status and plans

We present an overview of a research program for the excited nucleon states in Excited Baryon Analysis Center (EBAC) at Jefferson Lab. Current status of our analysis of the meson production reactions based on the unitary dynamical coupled-channels model is summarized, and the N* pole positions extracted from the constructed scattering amplitudes are presented. Our plans for future developments are also discussed.Comment: Plenary talk given at Workshop on the Physics of Excited Nucleon -- NSTAR2009, Beijing, April 19-22, 2009. 8 pages, 8 figure

Near-threshold ω\omega-meson production in proton-proton collisions: With or without resonance excitations ?

We present results for the $p p \to p p \omega$ reaction studied by considering two different scenarios: with and without the inclusion of nucleon resonance excitations. The recently measured angular distribution by the COSY-TOF Collaboration at an excess energy of $Q = 173$ MeV and the energy dependence of the total cross section data for $\pi^- p \to \omega n$ are used to calibrate the model parameters. The inclusion of nucleon resonances improves the theoretical prediction for the energy dependence of the total cross section in $pp \to pp\omega$ at excess energies $Q < 31$ MeV. However, it still underestimates the data by about a factor of two, and remains a problem in understanding the reaction mechanism.Comment: Fig.5 and text modified, Latex, 4 pages, 8 embedded figures, uses espcrc1.sty (included), talk presented at PANIC02, Osaka, Japan, 30 September - 4 October 200

The influence of weather regimes on European renewable energy production and demand

The growing share of variable renewable energy increases the meteorological sensitivity of power systems. This study investigates if large-scale weather regimes capture the influence of meteorological variability on the European energy sector. For each weather regime, the associated changes to wintertime -mean and extreme- wind and solar power production, temperature-driven energy demand and energy shortfall (residual load) are explored. Days with a blocked circulation pattern, i.e. the Scandinavian Blocking and NAO negative regimes, on average have lower than normal renewable power production, higher than normal energy demand and therefore, higher than normal energy shortfall. These average effects hide large variability of energy parameters within each weather regime. Though the risk of extreme high energy shortfall events increases in the two blocked regimes (by a factor of 2.0 and 1.5, respectively), it is shown that such events occur in all regimes. Extreme high energy shortfall events are the result of rare circulation types and smaller-scale features, rather than extreme magnitudes of common large-scale circulation types. In fact, these events resemble each other more strongly than their respective weather regime mean pattern. For (sub-)seasonal forecasting applications weather regimes may be of use for the energy sector. At shorter lead times or for more detailed system analyses, their ineffectiveness at characterising extreme events limits their potential

Doing data analysis

'Research is about more than empirical evidence, but evidence is at the heart of finding out more about the social and education world. One way of marshalling evidence on a topic, or to answer a research question, is to use the findings of others as published in the literature. This use of evidence at third-hand is common – in the notorious literature review for a PhD, for example. I say ‘third-hand’ because the analyst does not have access to the primary evidence, nor are they re-presenting an analysis of the data. They are presenting a summary of what a previous author presented about an analysis of data. Done well, with a clear focus, such a review of literature can be useful, at least in establishing what others think, how a topic is usually researched, and why the topic might be important to research further. Some of the inherent weaknesses of using the accounts of others might be overcome by ensuring that all of the relevant literature was used, even accounts of unsuccessful studies and evidence from unpublished studies, and then conducting a full meta-analysis of the results (I recommend using a Bayesian approach, see appendix to Gorard et al. 2004, which allows the relatively simple combination of different kinds of evidence). But such systematic reviews of evidence are rare, very difficult to do properly, and both expensive and time-consuming. And anyway this second approach does not overcome the chief drawbacks of the literature which are that we have no direct access to the evidence of others, and often face a very partial view of the assumptions made and the analyses conducted.