Assessment of school performance through a multilevel latent Markov Rasch model

An extension of the latent Markov Rasch model is described for the analysis of binary longitudinal data with covariates when subjects are collected in clusters, e.g. students clustered in classes. For each subject, the latent process is used to represent the characteristic of interest (e.g. ability) conditional on the effect of the cluster to which he/she belongs. The latter effect is modeled by a discrete latent variable associated with each cluster. For the maximum likelihood estimation of the model parameters we outline an EM algorithm. We show how the proposed model may be used for assessing the development of cognitive Math achievement. This approach is applied to the analysis of a dataset collected in the Lombardy Region (Italy) and based on test scores over three years of middle-school students attending public and private schools

Functionalisation of colloidal transition metal sulphides nanocrystals: A fascinating and challenging playground for the chemist

Metal sulphides, and in particular transition metal sulphide colloids, are a broad, versatile and exciting class of inorganic compounds which deserve growing interest and attention ascribable to the functional properties that many of them display. With respect to their oxide homologues, however, they are characterised by noticeably different chemical, structural and hence functional features. Their potential applications span several fields, and in many of the foreseen applications (e.g., in bioimaging and related fields), the achievement of stable colloidal suspensions of metal sulphides is highly desirable or either an unavoidable requirement to be met. To this aim, robust functionalisation strategies should be devised, which however are, with respect to metal or metal oxides colloids, much more challenging. This has to be ascribed, inter alia, also to the still limited knowledge of the sulphides surface chemistry, particularly when comparing it to the better established, though multifaceted, oxide surface chemistry. A ground-breaking endeavour in this field is hence the detailed understanding of the nature of the complex surface chemistry of transition metal sulphides, which ideally requires an integrated experimental and modelling approach. In this review, an overview of the state-of-the-art on the existing examples of functionalisation of transition metal sulphides is provided, also by focusing on selected case studies, exemplifying the manifold nature of this class of binary inorganic compounds

Social Interaction in Patients'�Hospital Choice: Evidences from Italy

In this paper we study the influence of social interaction on patients' hospital choice and its relationship with quality delivered by hospitals, using Italian data. We explore the impact on individual choices of a set of variables such as travel distance, individual- and hospital-specific characteristics, as well as a variable capturing the effect of the neighbourhood. The richness of our data allows us to disentangle contextual effects from the influence of information sharing on patients' hospital choices. We then use this framework to assess how such interaction is related to clinical hospital quality. Results show that network effect plays an important role in hospital choices, although it is less relevant for larger hospitals. Another empirical finding is the existence of a negative relationship between the degree of interaction among individuals and the quality delivered by hospitals. The absence of a source of information on the quality of hospitals accessible to all individuals, such as guidelines or star ratings, exacerbates the importance of information gathered locally in hospital choices, which may result in a lower degree of competition among hospitals and lower quality.health care, social interaction, quality

Local Statistical Modeling via Cluster-Weighted Approach with Elliptical Distributions

Cluster Weighted Modeling (CWM) is a mixture approach regarding the modelisation of the joint probability of data coming from a heterogeneous population. Under Gaussian assumptions, we investigate statistical properties of CWM from both the theoretical and numerical point of view; in particular, we show that CWM includes as special cases mixtures of distributions and mixtures of regressions. Further, we introduce CWM based on Student-t distributions providing more robust fitting for groups of observations with longer than normal tails or atypical observations. Theoretical results are illustrated using some empirical studies, considering both real and simulated data.Cluster-Weighted Modeling, Mixture Models, Model-Based Clustering

The effects of upcoding, cream skimming and readmissions on the Italian hospitals efficiency: a population–based investigation

In this paper we analyze the effects of some distortions induced by prospective payment system, i.e. Upcoding, Cream Skimming and Readmissions, on hospitals’ technical efficiency. We estimate a production function using a population–based dataset composed by all active hospitals in an Italian region during the period 1998–2007. We show that cream skimming and upcoding have a negative impact on hospitals’ technical efficiency, while readmissions have a positive effect. Moreover, we find that private hospitals are more engaged in cream skimming than public and not–for–profit ones, while we observe no ownership differences regarding upcoding. Not–for–profit hospitals have the highest readmission index. Last, not–for–profit and public hospitals have the same efficiency levels, while private hospitals have the lowest technical efficiency.Upcoding, Cream Skimming, Readmission, Hospital Technical Efficiency, Ownership.

On the Relationships among Latent Variables and Residuals in PLS Path Modeling: the Formative-Reflective Scheme

A new approach for the estimation and the validation of a Structural Equation Model with a formative-reflective scheme is presented. The basis of the paper is a proposal for overcoming a potential deficiency of PLS Path Modeling. In the PLS approach the reflective scheme assumed for the endogenous latent variables is inverted; moreover, the model errors are not explicitly taken into account for the estimation of the endogenous latent variables. The proposed approach utilizes all the relevant information in the formative manifest variables providing solutions which respect the causal structure of the model. The estimation procedure is based on the optimization of the redundancy criterion. The new approach, entitled Redundancy Analysis approach to Path Modeling is compared with both traditional PLS Path Modeling and LISREL methodology, on the basis of real and simulated data.Latent Variables, Partial Least Squares, PLS Path Modeling, Redundancy Analysis, LISREL Model

Designing food structure to slow down digestion in starch-rich products

The category of starch-rich foods is on the spot for its role in the development of obesity and related diseases. Therefore, the priority of modern food industry. In this paper, three different food design strategies that can be used to modulate the release of glucose during the gastrointestinal process of starch-rich foods, are illustrated. The structure of the starch granules can be modified by controlling processing parameters (i.e. moisture, temperature and shear) thus influencing the gelatinization and retrogradation behavior. The intactness of plant cell walls hindering the access of amylases to the starch granules and the formation of a stiffed food matrix using the crosslinking between proteins and the melanoidins generated by Maillard reaction are also very effective approaches. Following these food design strategies several practical approaches can be pursued by food designers to find reliable solutions combining the consumers request of palatable and rewarding foods with the public health demand of having food products with better nutritional profile

EPMA position paper in cancer:current overview and future perspectives

At present, a radical shift in cancer treatment is occurring in terms of predictive, preventive, and personalized medicine (PPPM). Individual patients will participate in more aspects of their healthcare. During the development of PPPM, many rapid, specific, and sensitive new methods for earlier detection of cancer will result in more efficient management of the patient and hence a better quality of life. Coordination of the various activities among different healthcare professionals in primary, secondary, and tertiary care requires well-defined competencies, implementation of training and educational programs, sharing of data, and harmonized guidelines. In this position paper, the current knowledge to understand cancer predisposition and risk factors, the cellular biology of cancer, predictive markers and treatment outcome, the improvement in technologies in screening and diagnosis, and provision of better drug development solutions are discussed in the context of a better implementation of personalized medicine. Recognition of the major risk factors for cancer initiation is the key for preventive strategies (EPMA J. 4(1):6, 2013). Of interest, cancer predisposing syndromes in particular the monogenic subtypes that lead to cancer progression are well defined and one should focus on implementation strategies to identify individuals at risk to allow preventive measures and early screening/diagnosis. Implementation of such measures is disturbed by improper use of the data, with breach of data protection as one of the risks to be heavily controlled. Population screening requires in depth cost-benefit analysis to justify healthcare costs, and the parameters screened should provide information that allow an actionable and deliverable solution, for better healthcare provision