Use of Poset Theory with Big Datasets: A New Proposal Applied to the Analysis of Life Satisfaction in Italy

The aim of this work is to propose a tool for measuring a complex concept, and to apply it to big sets of data measured on ordinal and/or dichotomous scales. An important field of application are subjective data, that are often based on opinions or personal evaluations. Many national and international surveys employ this kind of data, measured among thousand of individuals. Thanks to the use of the “average rank” as a synthetic measure of a complex concept, we believe that poset theory could be a very useful approach for dealing with ordinal data avoiding the use of scaling procedures. Because classic poset approaches are at their best when applied to few data at a time, our idea is based on a procedure for sampling units from a big population using a simple criterion to summarize the resulting values appropriately. Applying the central limit theorem enables a comparison of the results obtained from different groups using statistical tests on the means. We used our Height of Groups by Sampling (HOGS) method to compare the average rank among groups that are defined by one or more socio-demographic variables influencing the level of the complex concept we wish to measure. The application of the HOGS procedure to life satisfaction in Italy generated convincing results, revealing significant differences between regions, genders and levels of formal education. We compared the results given by HOGS with the non linear principal component analysis and obtain an easy readable output with convincing precision and accuracy; we are confident that the HOGS procedure can be applied to many other concepts investigated in the social sciences.     

A Mixed Model-assisted Regression Estimator that Uses Variables Employed at the Design Stage

The Generalized regression estimator (GREG) of a finite population mean or total has been shown to be asymptotically optimal when the working linear regression model upon which it is based includes variables related to the sampling design. In this paper a regression estimator assisted by a linear mixed superpopulation model is proposed. It accounts for the extra information coming from the design in the random component of the model and saves degrees of freedom in finite sample estimation. This procedure combines the larger asymptotic efficiency of the optimal estimator and the greater finite sample stability of the GREG. Design based properties of the proposed estimator are discussed and a small simulation study is conducted to explore its finite sample performance.     

Time as a limited resource: Communication strategy in mobile phone networks

We used a large database of 9 billion calls from 20 million mobile users to examine the relationships between aggregated time spent on the phone, personal network size, tie strength and the way in which users distributed their limited time across their network (disparity). Compared to those with smaller networks, those with large networks did not devote proportionally more time to communication and had on average weaker ties (as measured by time spent communicating). Further, there were not substantially different levels of disparity between individuals, in that mobile users tend to distribute their time very unevenly across their network, with a large proportion of calls going to a small number of individuals. Together, these results suggest that there are time constraints which limit tie strength in large personal networks, and that even high levels of mobile communication do not fundamentally alter the disparity of time allocation across networks.     

Electing a parliament

We present a model where a society elects candidates belonging to two parties to a national parliament. The electoral rule determines the seats distribution between the two parties. The policy outcome is a function of the number of seats the two parties win in the election. We analyze two electoral rules, multidistrict majority and single district proportional. We prove that under both systems there is a unique pure strategy perfect equilibrium outcome. We compare the outcomes under the two systems.     

The effect of corporate governance on sustainability disclosure

Drawing on stakeholder theory, this paper examines the relationship of board composition, leadership and structure on sustainability disclosure. We discuss that good corporate governance and sustainability disclosure can be seen as complementary mechanisms of legitimacy that companies may use to dialogue with stakeholders. Specifically we claim that, as disclosure policies emanate from the board of directors, sustainability disclosure may be a function of the board attributes: we investigate the relationship between different characteristics of the board and sustainability disclosures among US and European companies. Our results show that in order to explain the effect of board composition on sustainability disclosure we need to go beyond the narrow and traditional distinction between insider and independent directors, focusing on the specific characteristics of each director.     

Problems of Measurement of the Relationship Between Civil Society and Democracy When Using Survey Data

Social Indicators Research - Over the last three decades, it has become accepted wisdom that membership in civil society organizations enhances civic participation and encourages democratic...     

Nonparametric semi-supervised classification with application to signal detection in high energy physics

Statistical Methods & Applications - Model-independent searches in particle physics aim at completing our knowledge of the universe by looking for new possible particles not predicted by the...