Multivariate outlier detection in incomplete survey data: the epidemic algorithm and transformed rank correlations

Summary.  As a part of the EUREDIT project new methods to detect multivariate outliers in incomplete survey data have been developed. These methods are the first to work with sampling weights and to be able to cope with missing values. Two of these methods are presented here. The epidemic algorithm simulates the propagation of a disease through a population and uses extreme infection times to find outlying observations. Transformed rank correlations are robust estimates of the centre and the scatter of the data. They use a geometric transformation that is based on the rank correlation matrix. The estimates are used to define a Mahalanobis distance that reveals outliers. The two methods are applied to a small data set and to one of the evaluation data sets of the EUREDIT project.     

Robust, distribution-free inference for income share ratios under complex sampling

The quintile share ratio of disposable income is the primary inequality indicator of the European Union. As an inequality indicator, it must be sensitive to extreme large observations. Therefore, outliers have a strong impact on the bias and the variance of the classical quintile share ratio estimator. This may mislead the interpretation of income inequality. A class of estimators which are robust against outliers is introduced. They have a bounded influence function, they may reduce the bias incurred by the robustification and they reduce variability. Based on an asymptotic framework which respects the design-based, non-parametric approach, inference for these robust estimators is developed. A large simulation study with close to reality universes derived from the Statistics of Living Conditions Surveys of the EU allows to study the performance of the proposed estimators.     

Code choice and code-switching in Swiss-German Internet Relay Chat rooms

In the German-speaking regions of Switzerland, dialect is spoken by all social groups in most communicative situations, Standard German being used only when prescribed. Swiss dialects rarely appeared in written form before the 1980s, apart from the genre of dialect literature. Due to the growing acceptance of informal writing styles in many European languages, dialect is increasingly employed for written personal communication, in particular in computer-mediated communication (CMC). In Swiss Internet Relay Chat (IRC) rooms, varieties of German are used side by side as all chatters have a command of both standard and dialectal varieties. Depending on the channel, the proportion of dialectal contributions can be as high as 90 percent. The choice of a particular variety depends on both individual preference and on the predominant variety used within a specific thread. In this paper I take a quantitative approach to language variation in IRC and demonstrate how such an approach can help embed qualitative research on code-switching in CMC.     

Single machine batch scheduling with release times

Motivated by a high-throughput logging system, we investigate the single machine scheduling problem with batching, where jobs have release times and processing times, and batches require a setup time. Our objective is to minimize the total flow time, in the online setting. For the online problem where all jobs have identical processing times, we propose a 2-competitive algorithm and we prove a corresponding lower bound. Moreover, we show that if jobs with arbitrary processing times can be processed in any order, any online algorithm has a linear competitive ratio in the worst case. A preliminary version of a part of this paper was presented at the 31st International Symposium on Mathematical Foundations of Computer Science (MFCS 2006). We gratefully acknowledge reviewers’ comments that helped to improve the presentation of this work. Supported by the Swiss SBF under contract no. C05.0047 within COST-295 (DYNAMO) of the European Union. Research carried out while B. Weber was affiliated with the Institute of Theoretical Computer Science, ETH Zurich.     

Robust exchangeability designs for early phase clinical trials with multiple strata

Clinical trials with multiple strata are increasingly used in drug development. They may sometimes be the only option to study a new treatment, for example in small populations and rare diseases. In early phase trials, where data are often sparse, good statistical inference and subsequent decision‐making can be challenging. Inferences from simple pooling or stratification are known to be inferior to hierarchical modeling methods, which build on exchangeable strata parameters and allow borrowing information across strata. However, the standard exchangeability (EX) assumption bears the risk of too much shrinkage and excessive borrowing for extreme strata. We propose the exchangeability–nonexchangeability (EXNEX) approach as a robust mixture extension of the standard EX approach. It allows each stratum‐specific parameter to be exchangeable with other similar strata parameters or nonexchangeable with any of them. While EXNEX computations can be performed easily with standard Bayesian software, model specifications and prior distributions are more demanding and require a good understanding of the context. Two case studies from phases I and II (with three and four strata) show promising results for EXNEX. Data scenarios reveal tempered degrees of borrowing for extreme strata, and frequentist operating characteristics perform well for estimation (bias, mean‐squared error) and testing (less type‐I error inflation). Copyright © 2015 John Wiley & Sons, Ltd.     

Alien aquatic plants in wetlands of a large European city (Geneva,Switzerland): from diagnosis to risk assessment

Urban Ecosystems - Wetlands often form an important component in the urban matrix, where they are largely disseminated. Despite the abundance of these urban waterbodies, little is known about the...     

The effect of aging on pacing strategies of cross-country skiers and the role of performance level

Background

The participation of master cross-country (XC) skiers in training and competition has increased during the last decades; however, little is known yet about whether these athletes differ from their younger counterparts in aspects of performance such as pacing. Therefore, the aim of the present study was to examine the combined effect of age and performance (race time) on pacing in cross-country (XC) skiing. We analyzed all finishers (n?=?79,722) in ‘Vasaloppet’ from 2012 to 2017, the largest cross-country skiing race in the world, classified according to their race time into 10 groups: 3-4 h, 4-5 h, ..., 12-13 h.

Results

A trivial main effect of sex on total pace range was observed (p?<?0.001, η²?=?0.002), where women (44.1?±?10.2%) had larger total pace range than men (40.9?±?11.8%). A large main effect of performance group on total pace range was shown (p?<?0.001, η²?=?0.160), where the smallest total pace range was 21.8?±?1.9% (3-4 h group) and the largest 50.1?±?9.9% (10-11 h group). A trivial sex×performance group interaction on total pace range was found (p?<?0.001, η²?=?0.001) with the largest sex difference in pacing shown in 9-10 h group. A trivial and small main effect of age was found in women (p?<?0.001, η²?=?0.005) and men (p?<?0.001, η²?=?0.011), respectively, where the masters had smaller total pace range than their younger counterparts. A trivial age group×performance group interaction on total pace range was observed in both women (p?<?0.001, η²?=?0.008) and men (p?<?0.001, η²?=?0.006) with smaller differences among age groups in the faster performance groups.

Conclusions

In summary, master XC skiers adopted a relatively even pacing independently from their race time and the differences in pacing from the younger XC skiers were more pronounced in the slower masters. These findings suggest that exercise attenuates the decline of performance in master XC skiers as shown by the similar pacing strategies between fast master XC skiers and their younger counterparts.