STATISTICA & APPLICAZIONI
Six-monthly journal aimed at promoting research in the Methodological Statistics field
Statistica & Applicazioni is a six-monthly journal aimed at promoting research in statistical methodology and its original and innovative applications. Statistica & Applicazioni publishes research articles (and short notes) on theoretical, computational and applied statistics.
The journal is Open Access.
The journal was founded in 2003 by the following Departments belonging to different Italian Universities:
- Quantitative Methods - University of Brescia;
- Quantitative Methods for Business and Economic Sciences - University of Milano-Bicocca;
- Statistics - University of Milano-Bicocca;
- Information Technology and Mathematical Methods - University of Bergamo;
- Economics and Statistics - University of Calabria;
- «Silvio Vianelli» Mathematical and Statistical Sciences - University of Palermo;
- Statistics - Catholic University of the Sacred Heart, Milan.
At present the journal is supported by the following organizations:
- DMS StatLab - University of Brescia
- Department of Statistics and Quantitative Methods - University of Milano-Bicocca
- Department of Statistics - Catholic University of the Sacred Heart, Milan
- Department of Economics, Statistics and Finance - University of Calabria
- Department of Engineering - University of Bergamo
- Az.Agr.Case Basse of Gianfranco Soldera
- Indexed in: Scopus - Current Index to Statistics - Ulrich's Periodicals Directory - SCImago Journal & Country Rank
- Available on: Torrossa - EBSCO Discovery Service
In this issue
C o n t e n t s
Application of the Zenga distribution to the analysis of household income in Poland by socio-economic group
Zenga distribution is a new income distribution model which possesses interesting statistical properties and can be fitted to various empirical wage and income distributions. In the paper an attempt of an application of the model to income distributions in Poland by socio-economic groups is presented. The basis for the calculation was the micro data coming from the HBS sample provided by the Statistics Poland. The results of the calculations confirm that the Zenga distribution is a good income distribution model which can be successfully applied to income inequality analysis and income distribution comparisons.
Quality evaluation in healthcare has obtained a growing attention in the statistical literature. In order to evaluate hospital performances by comparing hospital outcomes it is necessary to remove the bias due to the different case-mix in each hospital, which is usually done using statistical modeling as a risk adjustment tool. Template matching is a new matching approach allowing to remove bias selection in a multi-treatment setting, resulting in a clean and easily interpretable evaluation. We adopted this method to compare caesarean section rates across the hospitals of two Italian regions: Sardinia and Lombardy. We found 5 (out of 79) hospitals with abnormal performance on the same template of expectant mothers, and all these hospitals are located in Lombardy, whereas we do not observe a relationship with the number of deliveries per year and the ownership. Despite this, fairness of the comparing procedure makes easier for the policy makers the identification of potential outliers with respect to both patients’ selection and outcomes.
by Enrico Ciavolino, Giada Coletta, Lara Colombo, Claudio Giovanni Cortese, Emanuela Ingusci, Isabel Rodriguez, Fulvio Signore, Nuria Tordera, Margherita Zito pages: 21 Download
Research on job crafting is increasing nowadays. Job crafting has been studied in terms of a mediator variable useful to improve positive organizational behaviors, and it has crucial theoretical and practical implications. In order to facilitate its measurement in large surveys, in different settings, we aimed to develop a brief 12-item version, the Job Crafting Scale-Short Form (JCS-SF). Having a brief scale to measure job crafting behaviors will contribute to facilitate research in several organizational contexts. This study presents the main psychometric properties of a brief JC scale based on JC scale developed by Tims et al. (2012). EFA results show support for the original Four-factor solution. Results have been confirmed using CFA. The four subscales showed adequate reliability. The brief scale could be used for researchers and practitioners in public and private organizational sectors.
In this paper a simulation study is carried out to compare the power of a new test derived from the Gini’s index of dispersion of the spacings with some well-known tests of uniformity against the standard alternatives such as the Beta family, Lehmann type alternatives and Tukey’s family of distributions. In this simulation special attention is devoted to the values of the parameters corresponding to low, moderate and high value of the Kullback-Leibler (KL) distance from the uniform. Next some asymptotically locally most powerful tests, in addition to locally most powerful test for normal sequence of location alternatives, are described. For the simulated power comparison of these with the above test, members from each of the three families of densities given in Quesenberry and Miller with small and large KL distance from uniform are selected.
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