Ida Camminatiello

Cumulative Correspondence Analysis of Two-Way Ordinal Contingency Tables

A suitable measure of association for two ordered variables is the doubly cumulative chi-squared statistic (Hirotsu, 1994). This statistic is obtained by considering the cumulative sum of cell frequencies across the variables. In this article, we explore the development of correspondence analysis which takes into account the presence of two ordered variables by partitioning the doubly cumulative chi-squared statistic.

The association in a two-way contingency table through log odds ratio analysis: the case of Sarno river pollution

In this paper we are proposing a general framework for the analysis of the complete set of log Odds Ratios (ORs) generated by a two-way contingency table. Starting from the RC (M) association model and hypothesizing a Poisson distribution for the counts of the two-way contingency table we are obtaining the weighted Log Ratio Analysis that we are extending to the study of log ORs. Particularly we are obtaining an indirect representation of the log ORs and some synthesis measures. Then for studying the matrix of log ORs we are performing a generalized Singular Value Decomposition that allows us to obtain a direct representation of log ORs. We also expect to get summary measures of association too. We have considered the matrix of complete set of ORs, because, it is linked to the two-way contingency table in terms of variance and it allows us to represent all the ORs on a factorial plan. Finally, a two-way contingency table, which crosses pollution of the Sarno river and sampling points, is to be analyzed to illustrate the proposed framework.

Objective Measurements of Student Satisfaction by Comparing the Effects of Different Factors

Abstract Item Response Theory (IRT) is proposed in literature for evaluating the customer satisfaction in private and public service. In this work a particular version of IRT, known as Partial Credit Model (PCM), is proposed to analyse the satisfaction of university students of a middle university of Southern Italy. Moreover, to consider the effects of different factors (degree course, departments, presence of integrative teaching activities, etc) and their interactions, factorial differential item functioning proposed for the Rasch model is extended to PCM.