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A New Index for the Comparison of Different Measurement Scales
No full textIn psychometric sciences, a common problem is the choice of a good response
scale. Every scale has, by its nature, a propensity to lead a respondent to
mainly positive -or negative- ratings. This paper investigates possible causes of the
discordance between two ordinal scales evaluating the same goods or services. In
psychometric literature, Cohen’s Kappa is one of the most important index to evaluate
the strength of agreement, or disagreement, between two nominal variables, in
particular in its weighted version. In this paper, a new index is proposed. A proper
procedure to determine the lower and upper triangle in a non-square table is also
implemented, as to generalize the index in order to compare two scales with a different
number of categories. A test is set up with the aim to verify the tendency of
a scale to have a different rating compared to a different one. A study with real data
is conducted
Editorial Issue 2/2012
No full textThis second issue of volume 6 (2012) of the journal Advances in Data Analysis
and Classification (ADAC) comprises four articles which deal with dissimilarity and
similarity measures for comparing dendrograms, robust clustering, orthogonal rotation
in a principal component method for a mixture of qualitative and quantitative variables,
and the symbolic analysis of histogram data by means of a modified interval principal
component analysis (PCA). Proposed methods are usually illustrated by real-case or
simulated example
Editorial for issue 4/2019
No full textThis is the Editorial of Issue 4 of 2019. Several papers have been analyse
Editorial for issue 3 2015
No full textThis third issue volume 9 (2015) of the journal Advances in Data Analysis and Classification (ADAC) includes articles which deal with: a biplot procedure after clustering objects and variables; an extension of classical principal component analysis to the case of non-linear reconstruction formulas (auto-associative models); a nonparametric fast and very robust new classifier, named DDα
-classifier; and a clustering methodology for financial time series; finally a diffusion model for churn prediction based on sociometric theory
Editorial Issue 2/2014
No full textThe second issue of volume 8 (2014) of the journal Advances in Data Analysis and Classification (ADAC) includes articles which deal with: a comparison of various information criteria used to select the number of latent states of a multivariate latent Markov model; a new methodology for visualizing, on a dimension reduced subspace, the classification structure and the geometric characteristics of an estimated Gaussian mixture model in discriminant analysis; parameter estimation for model-based clustering in the case of a finite mixture of normal inverse Gaussian (NIG) distributions; a discrimination approach for separating, in gamma-ray astronomy, the gamma-ray signal from a hadronic background; finally, a new simple majorization–minimization (MM) algorithm to solve certain types of optimization problems in multivariate analysis, e.g., a common principal components model for G
groups proposed by Flury. The proposed methods are illustrated by real-case or simulated examples
Editorial for issue 3/2017
No full textThe present issue 3 of volume 11 (2017) of the journal Advances in Data Analysis and Classification (ADAC) includes articles which deal with: robust classifiers for multivariate and functional data, constrained clustering, fuzzy neural clustering network, density based trajectory clustering, flower pollination search algorithm, algorithm to identify the prior probabilities for classification problem and general location model
Editorial 4/2014
No full textThis fourth issue of volume 8 (2014) of the journal Advances in Data Analysis and Classification (ADAC) includes four articles which are mainly devoted to the analysis of real-case data: a new methodology for clustering financial time series; a feature selection algorithm for classification in the problem of fault diagnosis; a comparison of five recursive partitioning methods to find person subgroups involved in meaningful treatment-subgroup interactions, and a latent class approach for analyzing the attitudes of Polish people on the adoption of the Euro
Editorial for issue 2/2015
No full textThis second issue of volume 9 (2019) of the journal Advances in Data Analysis and Classification (ADAC) includes articles which deal with: the correspondence analysis on a generalized aggregated lexical table (CA-GALT); new univariate and bivariate statistics for distributional variables in the framework of symbolic data analysis; the selection of a number of clusters that not only fits well the data, but simultaneously uses the potential illustrative ability of the available external variables in the model-based clustering context; a mixture model averaging for clustering; a simple nonlinear biplot that represents the marker points of a variable on a curved line that is governed by splines
Editorial for issue 3/2019
No full textThis is the Editorial of the Issue 3 of 2019. Several papers have been discusse
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