Outlyingness: Which variables contribute most?

Outlier detection is an inevitable step to most statistical data analyses. However, the mere detection of an outlying case does not always answer all scientific questions associated with that data point. Outlier detection techniques, classical and robust alike, will typically flag the entire case as outlying, or attribute a specific case weight to the entire case. In practice, particularly in high dimensional data, the outlier will most likely not be outlying along all of its variables, but just along a subset of them. If so, the scientific question why the case has been flagged as an outlier becomes of interest. In this article, a fast and efficient method is proposed to detect variables that contribute most to an outlier’s outlyingness. Thereby, it helps the analyst understand in which way an outlier lies out. The approach pursued in this work is to estimate the univariate direction of maximal outlyingness. It is shown that the problem of estimating that direction can be rewritten as the normed solution of a classical least squares regression problem. Identifying the subset of variables contributing most to outlyingness, can thus be achieved by estimating the associated least squares problem in a sparse manner. From a practical perspective, sparse partial least squares (SPLS) regression, preferably by the fast sparse NIPALS (SNIPLS) algorithm, is suggested to tackle that problem. The performed method is demonstrated to perform well both on simulated data and real life examples.

     

Movement strategy and performance in a high-volume order picking workstation

The design of a work station generally prescribes a global movement pattern of the operator, but also leaving some degrees of freedom regarding movement strategy. For a specific order picking work station, we studied the movement strategies, the underlying factors and its impact on performance. Eight subjects performed a task comprising, the picking and placing of an object and pressing a button in eight conditions varying in product weight, movement direction (left vs. right), and placing distance. Movements were analyzed and cycle times were obtained from video-recordings. We observed various types of strategy regarding hand use and global placing mode (reaching vs. placing). The different strategies did not show clear relationships with performance (in contrast to the various work place factors). Ergonomically spoken, the fact that the workstation allows movement variation without loss of performance, is favorable.     

Effects of vacation from work on health and well-being: Lots of fun,quickly gone

Abstract

Although vacation from work provides a valuable opportunity for recovery, few studies have met the requirements for assessing its effects. These include taking measurements well ahead of the vacation, during the vacation and at several points in time afterwards. Our study on vacation (after-) effects focused on two related questions: (1) Do health and well-being of working individuals improve during a vacation? and (2) How long does a vacation effect last after resumption of work? In a longitudinal study covering seven weeks, 96 Dutch workers reported their health and well-being levels two weeks before a winter sports vacation, during vacation and one week, two weeks and four weeks after vacation on seven indicators. Participants' health and well-being improved during vacation on five indicators: health status, mood, tension, energy level and satisfaction. However, during the first week of work resumption, health and well-being had generally returned to pre-vacation levels. In conclusion, a winter sports vacation is associated with improvements in self-reported health and well-being among working individuals. However, these effects fade out rapidly after work resumption. We propose a framework for future vacation research and suggest investigating the role of vacation type, duration and means to prolong vacation relief.     

Dimensions of work–home culture and their relations with the use of work–home arrangements and work–home interaction

Abstract

This study examined the associations of work–home culture with (a) demographic and organizational characteristics, (b) the use of work–home arrangements, and (c) negative and positive work–home interaction, among 1,179 employees from one public and two private organizations. Substantial support was found for a 2-factor structure of a work–home culture measure differentiating between “support” (employees’ perceptions of organization's, supervisors’, and colleagues’ responsiveness to work–family issues and to the use of work–home arrangements) and “hindrance” (employees’ perceptions of career consequences and time demands that may prevent them from using work–home arrangements). This 2-factor structure appeared to be invariant across organizations, gender, and parental status. Significant relationships with organizational characteristics, the use of work–home arrangements, and work–home interaction supported the validity of these two cultural dimensions. It is concluded that if employers want to minimize work–home interference, to optimize positive work–home interaction, and to boost the use of work–home arrangements, they should create a work–home culture that is characterized by high support and low hindrance.     

The relationships between work characteristics and mental health: examining normal, reversed and reciprocal relationships in a 4-wave study

This longitudinal study examined the causal relationships between job demands, job control and supervisor support on the one hand and mental health on the other. Whereas we assumed that work characteristics affect mental health, we also examined reversed causal relationships (mental health influences work characteristics). Further, the topic of the appropriate time lag for testing causal relationships was addressed. Our hypotheses were tested in a 4-wave study among a heterogeneous sample of 668 Dutch employees using structural equation modelling. The results provide evidence for reciprocal causal relationships between the work characteristics and mental health, although the effects of work characteristics on well-being were causally predominant. The best model fit was found for a 1-year time lag. Compared to earlier—predominantly cross-sectional—results, the present study presents a stronger case for the effects of work characteristics on the development of strain. The results also emphasize the need for a dynamic view of the relationship between work and health; the one-directional viewpoint in many work stress models does not seem to fully capture the relations between work characteristics and well-being.     

Social Support from Parents,Friends, Classmates,and Teachers in Children and Adolescents Aged 9 to 18 Years: Who Is Perceived as Most Supportive?

Age and gender differences in perceived social support from parents, friends, classmates, and teachers were investigated in 304 boys and 351 girls aged 9–18 years. The social support scale for children and adolescents was used for this purpose. Analyses showed that the level of perceived social support from parents and friends was similar across age groups. The study of the prominence of social support sources showed that parents and friends were perceived as equally supportive; only for the ages 16–18 years did friend support exceed parent support. Support from teachers was lower in the older age groups, and this was related to the transition from primary to secondary school. Finally, girls perceived more support from teachers, classmates and friends than boys did.     

Dimensions of work-home culture and their relations with the use of work-home arrangements and work-home interaction

This study examined the associations of work-home culture with (a) demographic and organizational characteristics, (b) the use of work-home arrangements, and (c) negative and positive work-home interaction, among 1,179 employees from one public and two private organizations. Substantial support was found for a 2-factor structure of a work-home culture measure differentiating between “support” (employees' perceptions of organization's, supervisors', and colleagues' responsiveness to work-family issues and to the use of work-home arrangements) and “hindrance” (employees' perceptions of career consequences and time demands that may prevent them from using work-home arrangements). This 2-factor structure appeared to be invariant across organizations, gender, and parental status. Significant relationships with organizational characteristics, the use of work-home arrangements, and work-home interaction supported the validity of these two cultural dimensions. It is concluded that if employers want to minimize work-home interference, to optimize positive work-home interaction, and to boost the use of work-home arrangements, they should create a work-home culture that is characterized by high support and low hindrance.