Models for Paired Comparison Data: A Review with Emphasis on Dependent Data

Thurstonian and Bradley-Terry models are the most commonly applied models in the analysis of paired comparison data. Since their introduction, numerous developments have been proposed in different areas. This paper provides an updated overview of these extensions, including how to account for object- and subject-specific covariates and how to deal with ordinal paired comparison data. Special emphasis is given to models for dependent comparisons. Although these models are more realistic, their use is complicated by numerical difficulties. We therefore concentrate on implementation issues. In particular, a pairwise likelihood approach is explored for models for dependent paired comparison data, and a simulation study is carried out to compare the performance of maximum pairwise likelihood with other limited information estimation methods. The methodology is illustrated throughout using a real data set about university paired comparisons performed by students.Comment: Published in at http://dx.doi.org/10.1214/12-STS396 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Empirical and Simulated Adjustments of Composite Likelihood Ratio Statistics

Composite likelihood inference has gained much popularity thanks to its computational manageability and its theoretical properties. Unfortunately, performing composite likelihood ratio tests is inconvenient because of their awkward asymptotic distribution. There are many proposals for adjusting composite likelihood ratio tests in order to recover an asymptotic chi square distribution, but they all depend on the sensitivity and variability matrices. The same is true for Wald-type and score-type counterparts. In realistic applications sensitivity and variability matrices usually need to be estimated, but there are no comparisons of the performance of composite likelihood based statistics in such an instance. A comparison of the accuracy of inference based on the statistics considering two methods typically employed for estimation of sensitivity and variability matrices, namely an empirical method that exploits independent observations, and Monte Carlo simulation, is performed. The results in two examples involving the pairwise likelihood show that a very large number of independent observations should be available in order to obtain accurate coverages using empirical estimation, while limited simulation from the full model provides accurate results regardless of the availability of independent observations.Comment: 15 page

Statistical modelling of citation exchange among statistics journals

Scholarly journal rankings based on citation data are often met with skepticism by the scientific community. Part of the skepticism is due to the discrepancy between the common perception of journals' prestige and their ranking based on citation counts. A more serious concern is the inappropriate use of journal rankings to evaluate the scientific influence of authors. This paper focuses on analysis of the table of cross-citations among a selection of Statistics journals. Data are collected from the Web of Science database published by Thomson Reuters. Our results suggest that modelling the exchange of citations between journals is useful to highlight the most prestigious journals, but also that journal citation data are characterized by considerable heterogeneity, which needs to be properly summarized. Inferential conclusions require care in order to avoid potential over-interpretation of insignificant differences between journal ratings

Gender mainstreaming at the local level: experiences of women’s empowerment in Barcelona and Umeå

openAt present the Agenda 2030 SDGs and the UN New Urban Agenda reiterate efforts for the achievement of gender equality globally, thus this research aims to present gender mainstreaming as an effective instrument for women’s empowerment at the local level with a view of promoting inclusive and sustainable urban development. Both international legal framework and feminist research on the advancement of women’s human rights will be taken into consideration to examine progress and gaps in policy. For the purpose of showcasing successful case studies of cities mainstreaming gender-sensitive policies and initiative, the urban areas of Barcelona and Umeå are identified as good practitioners for their commitment in the last decade to advance women’s empowerment on the ground, and for fostering participation and dialogue with local grassroots organisations.At present the Agenda 2030 SDGs and the UN New Urban Agenda reiterate efforts for the achievement of gender equality globally, thus this research aims to present gender mainstreaming as an effective instrument for women’s empowerment at the local level with a view of promoting inclusive and sustainable urban development. Both international legal framework and feminist research on the advancement of women’s human rights will be taken into consideration to examine progress and gaps in policy. For the purpose of showcasing successful case studies of cities mainstreaming gender-sensitive policies and initiative, the urban areas of Barcelona and Umeå are identified as good practitioners for their commitment in the last decade to advance women’s empowerment on the ground, and for fostering participation and dialogue with local grassroots organisations

Presentation S1-4: Breeding programs and a vailability of non-GM IP seeds for farmers in Brazil.

Soybean in Brazil. Soybean breeding program cf Embrapa. Embrapa policy regarding non-GM soybean program

Hybrid pairwise likelihood analysis of animal behavior experiments

The study of the determinants of contests between animals is an important issue in understanding animal behavior. Tournament experiments among a set of animals are used by zoologists for this purpose. From a statistical point of view, the results of these tournament experiments are naturally analyzed by paired comparison models such as the Bradley-Terry and the Thurstone models. A major complication is the presence of dependence between the outcomes of couples of contests with an animal in common. Likelihood analysis of this type of animal behavior experiments in presence of interdependence between contests is computationally demanding. An alternative fitting method that mixes optimal estimation equations and pairwise likelihood inference is then suggested. The performance of the proposed methodology is investigated by simulation studies and then applied to a real data set about adult male Cape Dwarf Chameleons

Modeling routing problems in QUBO with application to ride-hailing

Many emerging commercial services are based on the sharing or pooling of resources for common use with the aim of reducing costs. Businesses such as delivery-, mobility-, or transport-as-a-service have become standard in many parts of the world, fulfilling on-demand requests for customers in live settings. However, it is known that many of these problems are NP-hard, and therefore both modeling and solving them accurately is a challenge. Here we focus on one such routing problem, the Ride Pooling Problem (RPP), where multiple customers can request on-demand pickups and drop-offs from shared vehicles within a fleet. The combinatorial optimization task is to optimally pool customer requests using the limited set of vehicles, akin to a small-scale flexible bus route. In this work, we propose a quadratic unconstrained binary optimization (QUBO) program and introduce efficient formulation methods for the RPP to be solved using metaheuristics, and specifically emerging quantum optimization algorithms