Calibrating models in economic evaluation: a comparison of alternative measures of goodness of fit, parameter search strategies and convergence criteria.

BACKGROUND: The importance of assessing the accuracy of health economic decision models is widely recognized. Many applied decision models (implicitly) assume that the process of identifying relevant values for a model's input parameters is sufficient to prove the model's accuracy. The selection of infeasible combinations of input parameter values is most likely in the context of probabilistic sensitivity analysis (PSA), where parameter values are drawn from independently specified probability distributions for each model parameter. Model calibration involves the identification of input parameter values that produce model output parameters that best predict observed data. METHODS: An empirical comparison of three key calibration issues is presented: the applied measure of goodness of fit (GOF); the search strategy for selecting sets of input parameter values; and the convergence criteria for determining acceptable GOF. The comparisons are presented in the context of probabilistic calibration, a widely applicable approach to calibration that can be easily integrated with PSA. The appendix provides a user's guide to probabilistic calibration, with the reader invited to download the Microsoft® Excel-based model reported in this article. RESULTS: The calibrated models consistently provided higher mean estimates of the models' output parameter, illustrating the potential gain in accuracy derived from calibrating decision models. Model uncertainty was also reduced. The chi-squared GOF measure differentiated between the accuracy of different parameter sets to a far greater degree than the likelihood GOF measure. The guided search strategy produced higher mean estimates of the models' output parameter, as well as a narrower range of predicted output values, which may reflect greater precision in the identification of candidate parameter sets or more limited coverage of the parameter space. The broader convergence threshold resulted in lower mean estimates of the models' output, and slightly wider ranges, which were closer to the outputs associated with the non-calibrated approach. CONCLUSIONS: Probabilistic calibration provides a broadly applicable method that will improve the relevance of health economic decision models, and simultaneously reduce model uncertainty. The analyses reported in this paper inform the more efficient and accurate application of calibration methods for health economic decision models

The limit empirical spectral distribution of Gaussian monic complex matrix polynomials

We define the empirical spectral distribution (ESD) of a random matrix polynomial with invertible leading coefficient, and we study it for complex $n \times n$ Gaussian monic matrix polynomials of degree $k$. We obtain exact formulae for the almost sure limit of the ESD in two distinct scenarios: (1) $n \rightarrow \infty$ with $k$ constant and (2) $k \rightarrow \infty$ with $n$ constant. The main tool for our approach is the replacement principle by Tao, Vu and Krishnapur. Along the way, we also develop some auxiliary results of potential independent interest: we slightly extend a result by B\"{u}rgisser and Cucker on the tail bound for the norm of the pseudoinverse of a non-zero mean matrix, and we obtain several estimates on the singular values of certain structured random matrices.Comment: 25 pages, 4 figure

Simulation of coalescence, break up and mass transfer in bubble columns by using the Conditional Quadrature Method of Moments in OpenFOAM

The evaluation of the mass transfer rates and the fluid-dynamics aspects of bubble columns are strongly affected by the intrinsic poly-dispersity of the gas phase, namely the different dispersed bubbles are usually distributed over a certain range of size and chemical composition values. In our previous work, gas-liquid systems were investigated by coupling Computational Fluid Dynamics with mono-variate population balance models (PBM) solved by using the quadrature method of moments (QMOM). Since mass transfer rates depend not only on bubble size, but also on bubble composition, the problem was subsequently extended to the solution of multi-variate PBM (Buffo et al. 2013). In this work, the conditional quadrature method of moments (CQMOM) is implemented in the open-source code OpenFOAM for describing bubble coalescence, breakage and mass transfer of a realistic partially aerated rectangular bubble column, experimentally investigated by Diaz et al.(2008). Eventually, the obtained results are here compared with the experimental data availabl

Contexto de historias en la teoría cuántica

En la teoría cuántica, un contexto es un conjunto de propiedades que pueden considerarse simultáneamente en la descripción de un sistema. Las propiedades de un contexto fornan un retículado distributivo, y en cada estado del sistema poseen probabilidades bien definidas. Presentamos en este trabajo la noción de contexto de historias, una descripción de un sistema físico que puede incluir propiedades a distintos tiempos, a las que puede aplicarse la lógica convencional y asignarse probabilidades bien definidas. Postulamos un principio de contextualizad de historias y lo utilizamos para analizar el proceso de medición y el experimento de la doble ranura

El papel social de la publicidad

This paper analyses the behavior of advertising and the limites society tries to impose over it. This cogitation is made from a sociological perspective, due to the fact that it deals with the effects that advertising generates over social contexts and not over individual consumers

Riprogettazione e Miglioramento del Processo di Customer Satisfaction e dei suoi Strumenti: il caso BCUBE S.p.A.

Questo lavoro di tesi è il risultato del tirocinio svolto presso la business unit Energy di BCUBE dal 28 Luglio 2014 al 28 Aprile 2015. BCUBE è una realtà leader nell’offerta di servizi di logistica integrata per la gestione della supply chain, sia in ambito nazionale che internazionale. La divisione, vantando un ampio portafoglio clienti, tra cui la principale azienda Oil&Gas al mondo, e vivendo un periodo di forte crescita, ha la necessità di rilevare e misurare la soddisfazione dei propri clienti. L’obiettivo del progetto è dunque quello di riprogettare e migliorare il processo di customer satisfaction. A tal fine, le principali attività svolte sono state: l’analisi della business unit, la definizione del campione clienti da coinvolgere, l’interfacciamento con le varie software house per valutare la possibilità di esternalizzare il processo, la creazione del questionario e l’analisi delle risposte acquisite. I risultati ottenuti hanno permesso trasformare sentori e percezioni in dati di fatto in modo da permettere di intraprendere le dovute e opportune azioni di miglioramento continuo