A multilevel approach to the travelling salesman problem

We motivate, derive, and implement a multilevel approach to the travelling salesman problem.The resulting algorithm progressively coarsens the problem, initialises a tour, and then employs either the Lin-Kernighan (LK) or the Chained Lin-Kernighan (CLK) algorithm to refine the solution on each of the coarsened problems in reverse order.In experiments on a well-established test suite of 80 problem instances we found multilevel configurations that either improved the tour quality by over 25% as compared to the standard CLK algorithm using the same amount of execution time, or that achieved approximately the same tour quality over seven times more rapidly. Moreover, the multilevel variants seem to optimise far better the more clustered instances with which the LK and CLK algorithms have the most difficulties.

Is income area level associated with blood pressure in adults regardless of individual-level characteristics? A multilevel approach

This population-based health survey was carried out in Florianopolis, Brazil, to assess the association between adult systolic blood pressure (SBP) and contextual income level, after controlling for potential individual-level confounders. A statistically significant negative association between SBP levels and contextual income was identified after adjusting for individual-level characteristics. SBP levels in the highest and in the intermediate tertiles of contextual income were 5.78 and 2.82 mmHg lower, respectively, than that observed in the bottom tertile. The findings suggest an association between income area level and blood pressure, regardless of well-known individual-level hypertension risk factors. (C) 2012 Elsevier Ltd. All rights reserved.

Contextual and individual assessment of dental pain period prevalence in adolescents: a multilevel approach

Abstract Background Despite evidence that health and disease occur in social contexts, the vast majority of studies addressing dental pain exclusively assessed information gathered at individual level. Objectives To assess the association between dental pain and contextual and individual characteristics in Brazilian adolescents. In addition, we aimed to test whether contextual Human Development Index is independently associated with dental pain after adjusting for individual level variables of socio-demographics and dental characteristics. Methods The study used data from an oral health survey carried out in São Paulo, Brazil, which included dental pain, dental exams, individual socioeconomic and demographic conditions, and Human Development Index at area level of 4,249 12-year-old and 1,566 15-year-old schoolchildren. The Poisson multilevel analysis was performed. Results Dental pain was found among 25.6% (95%CI = 24.5-26.7) of the adolescents and was 33% less prevalent among those living in more developed areas of the city than among those living in less developed areas. Girls, blacks, those whose parents earn low income and have low schooling, those studying at public schools, and those with dental treatment needs presented higher dental-pain prevalence than their counterparts. Area HDI remained associated with dental pain after adjusting for individual level variables of socio demographic and dental characteristics. Conclusions Girls, students whose parents have low schooling, those with low per capita income, those classified as having black skin color and those with dental treatment needs had higher dental pain prevalence than their counterparts. Students from areas with low Human Development Index had higher prevalence of dental pain than those from the more developed areas regardless of individual characteristics.

Predicting Psychotherapy Dropouts: A Multilevel Approach

The role of therapeutic processes in predicting premature termination of psychotherapy has been a particular focus of recent research. The purpose of this study was to contrast outpatients who completed therapy and those who dropped out with respect to their self-reported in-session experiences of self-esteem, mastery, clarification and the therapeutic alliance. The 296 patients with mixed disorders were treated with an integrative form of cognitive–behavioural therapy without pre-determined time limit (M = 20.2 sessions). Multilevel analyses indicated that patients who did not completetreatment reported, on average, lower levels of self-esteem, mastery and clarification and lower ratings of their therapeutic alliance in treatment in contrast to patients who completed therapy. Patient-reported change in self-esteem experiences over the course of treatment turned out to be the strongest predictor of dropout from psychotherapy or successful completion. When dropout occurred before the average treatment length was reached, patients reported fewer clarifying experiences as early as the first session and their ratings of the therapeutic alliance were characterized by an absence of positive development. Both of these aspects seem to be involved in patients' decisions to leave treatment early. The findings underscore the importance of the therapeutic process in understanding the mechanisms behind treatment dropout. Copyright © 2014 John Wiley & Sons, Ltd.

A multilevel approach to the travelling salesman problem

Abstract not available

A multilevel investigation of inequalities in clinical and psychosocial outcomes for women after breast cancer

Background In Australia, breast cancer is the most common cancer affecting Australian women. Inequalities in clinical and psychosocial outcomes have existed for some time, affecting particularly women from rural areas and from areas of disadvantage. We have a limited understanding of how individual and area-level factors are related to each other, and their associations with survival and other clinical and psychosocial outcomes. Methods/Design This study will examine associations between breast cancer recurrence, survival and psychosocial outcomes (e.g. distress, unmet supportive care needs, quality of life). The study will use an innovative multilevel approach using area-level factors simultaneously with detailed individual-level factors to assess the relative importance of remoteness, socioeconomic and demographic factors, diagnostic and treatment pathways and processes, and supportive care utilization to clinical and psychosocial outcomes. The study will use telephone and self-administered questionnaires to collect individual-level data from approximately 3, 300 women ascertained from the Queensland Cancer Registry diagnosed with invasive breast cancer residing in 478 Statistical Local Areas Queensland in 2011 and 2012. Area-level data will be sourced from the Australian Bureau of Statistics census data. Geo-coding and spatial technology will be used to calculate road travel distances from patients' residence to diagnostic and treatment centres. Data analysis will include a combination of standard empirical procedures and multilevel modelling. Discussion The study will address the critical question of: what are the individual- or area-level factors associated with inequalities in outcomes from breast cancer? The findings will provide health care providers and policy makers with targeted information to improve the management of women with breast cancer, and inform the development of strategies to improve psychosocial care for women with breast cancer.

Change readiness : a multilevel review

The authors conducted a theoretical review of the change readiness literature and identified two major limitations with this work. First, while there is substantial agreement about the key cognitions that underlie change readiness, researchers have not examined the affective element of this attitude. Second, researchers have not adopted a multilevel perspective when considering change readiness. The authors address these limitations and argue that it is important to incorporate affect into definitions of the change readiness construct and also when measuring this construct. They then develop a multilevel framework that identifies the antecedents and consequences of individual, work group, and organizational change readiness. Next, the authors outline the theoretical processes that lead to the development of individual and collective change readiness. They then review theoretical and empirical evidence to identify the antecedents of change readiness at the three levels of analysis. Finally, the authors identify a number of suggestions to guide future research seeking to adopt a multilevel approach to change readiness.

Academic entrepreneurship: A multilevel examination of individual, subunit and organizational effects

This study utilizes a multilevel approach to both estimate the relative importance of individual, subunit, and organization effects on entrepreneurial intentions in academia, as well as to investigate specific factors within the subunit effect and their interactions with other levels. Using a dataset of 2,652 researchers from 386 departments in 24 European universities, our findings reveal that intra-university differences, caused by the influence of the department, should not be ignored when studying academic entrepreneurship. Whereas researchers’ entrepreneurial intentions are mostly influenced by individual differences, department membership explains more variation than the university as a whole. Furthermore, drawing upon organizational culture literature, we identify a department’s adhocracy culture, characterized by flexibility and an external orientation, to be positively related to entrepreneurial intentions. Finally, consistent with trait activation theory, we find that strong adhocracy cultures reinforce the positive association between proactive personality and entrepreneurial intentions. This effect is further intensified when the university also has a technology transfer office with a substantial size. Our results have relevant implications for both academics and practitioners, including university managers, department heads and policy makers.

Comparing multilevel and Bayesian spatial random effects survival models to assess geographical inequalities in colorectal cancer survival: a case study

Background Multilevel and spatial models are being increasingly used to obtain substantive information on area-level inequalities in cancer survival. Multilevel models assume independent geographical areas, whereas spatial models explicitly incorporate geographical correlation, often via a conditional autoregressive prior. However the relative merits of these methods for large population-based studies have not been explored. Using a case-study approach, we report on the implications of using multilevel and spatial survival models to study geographical inequalities in all-cause survival. Methods Multilevel discrete-time and Bayesian spatial survival models were used to study geographical inequalities in all-cause survival for a population-based colorectal cancer cohort of 22,727 cases aged 20–84 years diagnosed during 1997–2007 from Queensland, Australia. Results Both approaches were viable on this large dataset, and produced similar estimates of the fixed effects. After adding area-level covariates, the between-area variability in survival using multilevel discrete-time models was no longer significant. Spatial inequalities in survival were also markedly reduced after adjusting for aggregated area-level covariates. Only the multilevel approach however, provided an estimation of the contribution of geographical variation to the total variation in survival between individual patients. Conclusions With little difference observed between the two approaches in the estimation of fixed effects, multilevel models should be favored if there is a clear hierarchical data structure and measuring the independent impact of individual- and area-level effects on survival differences is of primary interest. Bayesian spatial analyses may be preferred if spatial correlation between areas is important and if the priority is to assess small-area variations in survival and map spatial patterns. Both approaches can be readily fitted to geographically enabled survival data from international settings

Parallel implementation of Multilevel BDDC

In application of the Balancing Domain Decomposition by Constraints (BDDC) to a case with many substructures, solving the coarse problem exactly becomes the bottleneck which spoils scalability of the solver. However, it is straightforward for BDDC to substitute the exact solution of the coarse problem by another step of BDDC method with subdomains playing the role of elements. In this way, the algorithm of three-level BDDC method is obtained. If this approach is applied recursively, multilevel BDDC method is derived. We present a detailed description of a recently developed parallel implementation of this algorithm. The implementation is applied to an engineering problem of linear elasticity and a benchmark problem of Stokes flow in a cavity. Results by the multilevel approach are compared to those by the standard (two-level) BDDC method.

Do obesity and sleep problems cluster in the workplace?:A multivariate, multilevel study

OBJECTIVES: The aim of this study was to examine the co-occurrence of obesity and sleep problems among employees and workplaces. METHODS: We obtained data from 39 873 men and women working in 3040 workplaces in 2000-2002 (the Finnish Public Sector Study). Individual- and workplace-level characteristics were considered as correlates of obesity and sleep problems, which were modelled simultaneously using a multivariate, multilevel approach. RESULTS: Of the participants, 11% were obese and 23% reported sleep problems. We found a correlation between obesity and sleep problems at both the individual [correlation coefficient 0.048, covariance 0.047, standard error (SE) 0.005) and workplace (correlation coefficient 0.619, covariance 0.068, SE 0.011) level. The latter, but not the former, correlation remained after adjustment for individual- and workplace-level confounders, such as age, sex, socioeconomic status, shift work, alcohol consumption, job strain, and proportion of temporary employees and manual workers at the workplace. CONCLUSIONS: Obese employees and those with sleep problems tend to cluster in the same workplaces, suggesting that, in addition to targeting individuals at risk, interventions to reduce obesity and sleep problems might benefit from identifying "risky" workplaces.