Complex Testing Problems for Multivariate Data and Small Sample Sizes: a Nonparanetric Approach.

The work proposes a methodological solution to complex testing problems. In particular, it is focused on two-sample or multi-sample tests in the presence of multivariate outcomes and very small sample sizes

It Sounds like It Feels: Preliminary Exploration of an Aeroacoustic Diagnostic Protocol for Singers

To date, no established protocol exists for measuring functional voice changes in singers with subclinical singing-voice complaints. Hence, these may go undiagnosed until they progress into greater severity. This exploratory study sought to (1) determine which scale items in the self-perceptual Evaluation of Ability to Sing Easily (EASE) are associated with instrumental voice measures, and (2) construct as proof-of-concept an instrumental index related to singers’ perceptions of their vocal function and health status. Eighteen classical singers were acoustically recorded in a controlled environment singing an /a/ vowel using soft phonation. Aerodynamic data were collected during a softly sung /papapapapapapa/ task with the KayPENTAX Phonatory Aerodynamic System. Using multi and univariate linear regression techniques, CPPS, vibrato jitter, vibrato shimmer, and an efficiency ratio (SPL/PSub) were included in a significant model (p < 0.001) explaining 62.4% of variance in participants’ composite scores of three scale items related to vocal fatigue. The instrumental index showed a significant association (p = 0.001) with the EASE vocal fatigue subscale overall. Findings illustrate that an aeroacoustic instrumental index may be useful for monitoring functional changes in the singing voice as part of a multidimensional diagnostic approach to preventative and rehabilitative voice healthcare for professional singing-voice users

Different views of the multivariate ranking problem

Multivariate ranking problems are characterized by the need of ordering C different items according to several different features. The multivariate nature of these problems makes them quite challenging and flexible multivariate statistical techniques are therefore required. In this study we focus on two different scenarios, where we need to rank C different populations. Under the first scenario, preliminary knowledge about the order of the populations is available, while under the second one no information is available. Two solutions, based on the Nonparametric combination (NPC) technique, are proposed to deal with these scenarios and two case studies are adopted to facilitate the comprehension of the methods and to highlights the main differences between the two considered multivariate ranking problems

Focussing crystals for use in broad band hard X/soft gamma-ray Laue lenses

Hard X-/soft gamma-ray astronomy is a crucial window for the study of the most energetic and violent events in the Universe. To fulfil the scientific requirements in this regime, a new generation of telescopes with a broad operational band extending from tens up to several hundreds of keV and exploiting unprecedented sensitivity (50-100 times better that current instruments) is required. We report on diffractive bent crystals made of Gallium Arsenide (GaAs) that are suitable for the construction of high sensitivity X-/gamma-ray Laue lens space telescopes. Laue lenses, made of sets of diffractive crystals working in transmission, offer one possibility, albeit technically challenging, to build a new generation of focusing telescopes that can extend the energy band far beyond the 80 keV limit for current multilayer concentrators. In particular, we present the results obtained from the characterization of crystals that will be used to realise a broad band Laue demonstrator. They have been studied in terms of focusing capability and diffraction efficiency by using a flat X-ray panel imager and an HPGe spectrometer as focal plane detectors. The GaAs tiles, bent via a surface lapping procedure, have been developed at the IMEM/CNR in Parma (Italy) in the framework of the LAUE project funded by the Italian Space Agency. The main goal of the project was to build a broad band Laue lens demonstrator for hard X-/soft gamma-rays (80-300 keV

Multivariate approach for comparative evaluations of customer satisfaction with application to transport services

In problems related to evaluations of products or services (e.g. in customer satisfaction analysis) the main difficulties concern the synthesis of the information, which is necessary for the presence of several evaluators and many response variables (aspects under evaluation). In this paper the problem of determining and comparing the satisfaction of different groups of customers, in the presence of multivariate response variables and using the results of pairwise comparisons is addressed. Within the framework of group ranking methods and multicriteria decision making theory, a new approach, based on nonparametric techniques, for evaluating group satisfaction in a multivariate framework is proposed and the concept of Multivariate Relative Satisfaction is defined. An application to the evaluation of public transport services, like the railways service and the urban bus service, by students of the University of Ferrara (Italy) is also discussed

Combined permutation tests and finite sample consistency

Combined Permutation Tests represent a nonparametric testing method in order to deal with a large number of variables, especially in the presence of small sample sizes. Under mild conditions the power of the test increases with the number of variables (finite sample consistency)

Testing for Heterogeneity with Categorical Data: Permutation Solution vs. Bootstrap Method

In this article the problem of comparing distributional heterogeneities for categorical variables is addressed. Specifically, the one-sided testing problem for heterogeneity comparisons is considered. For such a problem a bootstrap method is proposed and compared with a permutation method already present in literature. The power behavior of the two methods is compared through a Monte Carlo simulation study. The results of two real applications are shown

Two-sample multivariate test with high dimensional response

The work concerns problems where two independent samples (e.g. treated group and con- trol group) are compared in order to test the significance of a treatment effect. When the response is multivariate, likelihood based methods are difficult to be implemented and in many cases, expecially with small sample sizes, are not possible