Visualization of the Significant Explicative Categories using Catanova Method and Non-Symmetrical Correspondence Analysis for Evaluation of Passenger Satisfaction

ANalysis Of VAriance (ANOVA) is a method to decompose the total variation of the observations into sum of variations due to different factors and the residual component. When the data are nominal, the usual approach of considering the total variation in response variable as measure of dispersion about the mean is not well defined. Light and Margolin (1971) proposed CATegorical ANalysis Of VAriance (CATANOVA), to analyze the categorical data. Onukogu (1985) extended the CATANOVA method to two-way classified nominal data. The components (sums of squares) are, however, not orthogonal. Singh (1996) developed a CATANOVA procedure that gives orthogonal sums of squares and defined test statistics and their asymptotic null distributions. In order to study which exploratory categories are influential factors for the response variable we propose to apply Non-Symmetrical Correspondence Analysis (D'Ambra and Lauro, 1989) on significant components. Finally, we illustrate the analysis numerically, with a practical example

Estimating Accidents at Work in European Union

This paper describes safety at work as an issue to be addressed in terms of legislation, with due statistical knowledge of the phenomenon. Through the application of multiple indicators while investigating the rate of homogeneity and non-homogeneity of available data, especially at international level, the concept at study can be analyzed using specific scientific methods. The Total Frequency Rate of accidents could be influenced by a country’s industrial structure. The standardization of industrial structures into NACE divisions or sub-divisions (and not only on an aggregate activity level), has proved very useful as an integral part of the statistical infrastructure used within the European statistical system for producing comparable statistics. Looking at the distribution of the Total Frequency Rates (TFR) of accidents in different world regions, the picture is quite different, as the phenomenon is by no means evenly spread across the globe. Fatalities are proportionately much higher in some regions than in others. Carrying out a country-by-country analysis would in no doubt reveal greater variations. Occupational accidents and work-related diseases in some European countries are twice as high as in some others.We show that the shadow economy has an important impact in outlining an “effective frequency rate of accidents”. In Italy, the impact of an excessive economy and the influence of organized crime in the South, which could alter the basis for reporting work-related accidents and occupational safety performance indicators, has led to the consideration of the actual rate of accidents in Italy slightly higher than the European average

Estimating Accidents at Work in European Union

This paper describes safety at work as an issue to be addressed in terms of legislation, with due statistical knowledge of the phenomenon. Through the application of multiple indicators while investigating the rate of homogeneity and non-homogeneity of available data, especially at international level, the concept at study can be analyzed using specific scientific methods. The Total Frequency Rate of accidents could be influenced by a country’s industrial structure. The standardization of  industrial structures into NACE divisions or sub-divisions (and not only on an aggregate activity level), has proved very useful as an integral part of the statistical infrastructure used within the European statistical system for producing comparable statistics. Looking at the distribution of the Total Frequency Rates (TFR) of accidents in different world regions, the picture is quite different, as the phenomenon is by no means evenly spread across the globe. Fatalities are proportionately much higher in some regions than in others. Carrying out a country-by-country analysis would in no doubt reveal greater variations. Occupational accidents and work-related diseases in some European countries are twice as high as in some others.We show that the shadow economy has an important impact in outlining an “effective frequency rate of accidents”. In Italy, the impact of an excessive economy and the influence of organized crime in the South, which could alter the basis for reporting work-related accidents and occupational safety performance indicators, has led to the consideration of the actual rate of accidents in Italy slightly higher than the European average

Three-way ordinal non symmetrical correspondence analysis for the evaluation of the patient satisfaction

In some recent articles, emphasis has been given to the partition of the Goodman-Kruskal’s tau index using orthogonal polynomials for the study of the non symmetrical relations in three-way contingency tables. New graphical techniques that consider such a partition and allow for the analysis of asymmetric relationships have been proposed, including three-way ordinal non symmetrical correspondence analysis (Simonetti, 2003). Such a procedure takes into account the presence of an ordinal predictor and response variables. In this paper we demonstrate the applicability of such a technique for the patient satisfaction evaluation

Dimensionality reduction methods for contingency tables with ordinal variables

Correspondence analysis is a widely used tool for obtaining a graphical representation of the interdependence between the rows and columns of a contingency table, by using a dimensionality reduction of the spaces. The maximum information regarding the association between the two categorical variables is then visualized allowing to understand its nature. Several extensions of this method take directly into account the possible ordinal structure of the variables by using different dimensionality reduction tools. Aim of this paper is to present an unified theoretical framework of several methods of correspondence analysis with ordinal variables

Financial and real latent factors in forecasting economic time series

In this paper we want to assess the impact of real and financial variables in estimating smoothed GDP. We implement the generalized dynamic factor model, on which Eurocoin indicator is based. We assess that the impact of real and financial variables in estimating smoothed GDP, during the structural break in 2008, shows that the role of real data as industrial production, becomes particularly relevant in relation to that concerning financial data as money supply and spread. © 2012 Università del Salento

The real time ability of financial and real variables in nowcasting

In this paper we develop an approach to choose the variables useful for the nowcasting (short-term forecasting) of growth rate, that is based on the real time ability of financial and real variables to reproduce reference time series. We assess, for Germany and Italy, the impact of real and financial variables in estimating smoothed gross domestic product (GDP) from 2003 to 2012. In synthesis, the innovation of our work is the one to focus both on a limited number of series both on a large dataset of economic variables, by implementing the dynamic factor model

Technical efficiency with several stochastic frontier analysis models using panel data

The paper discusses technical efficiency analysis of italian rail terminals for a panel data from 2007 to 2011 considering variables related to production factors with a dynamic vision over time. To use of panel date makes the researchers think about whether inefficiency represented by the one-sided part of the error term varies true time or is constant true time. This paper use techniques, time varying and time invariant relating to estimation of stochastic production function and of technical effiency in order to analyze the production performance of rail road modal interchange terminal in Italy