Comparing Multilevel Clustering Methods on Weighted Graphs : The Case of Worldwide Air Passenger Traffic 2000-2004

Specific properties emerge from the structure of large networks, such as that of worldwide air traffic, including a highly hierarchical node structure and multi-level small world sub-groups that strongly influence future dynamics. We have developed clustering methods to understand the form of these structures, to identify structural properties, and to evaluate the effects of these properties. Graph clustering methods are often constructed from different components: a metric, a clustering index, and a modularity measure to assess the quality of a clustering method. To understand the impact of each of these components on the clustering method, we explore and compare different combinations. These different combinations are used to compare multilevel clustering methods to delineate the effects of geographical distance, hubs, network densities, and bridges on worldwide air passenger traffic. The ultimate goal of this methodological research is to demonstrate evidence of combined effects in the development of an air traffic network. In fact, the network can be divided into different levels of âeurooecohesionâeuro, which can be qualified and measured by comparative studies (Newman, 2002; Guimera et al., 2005; Sales-Pardo et al., 2007).

How Much Does It Cost? Optimization of Costs in Sequence Analysis of Social Science Data

One major methodological problem in analysis of sequence data is the determination of costs from which distances between sequences are derived. Although this problem is currently not optimally dealt with in the social sciences, it has some similarity with problems that have been solved in bioinformatics for three decades. In this article, the authors propose an optimization of substitution and deletion/insertion costs based on computational methods. The authors provide an empirical way of determining costs for cases, frequent in the social sciences, in which theory does not clearly promote one cost scheme over another. Using three distinct data sets, the authors tested the distances and cluster solutions produced by the new cost scheme in comparison with solutions based on cost schemes associated with other research strategies. The proposed method performs well compared with other cost-setting strategies, while it alleviates the justification problem of cost schemes.

Quality of Qualitative Research in the Health Sciences : Analysis of the Common Criteria Present in 58 Assessment Guidelines by Expert Users

The number of qualitative research methods has grown substantially over the last twenty years, both in social sciences and, more recently, in the health sciences. This growth came with questions on the quality criteria needed to evaluate this work, and numerous guidelines were published. The latters include many discrepancies though, both in their vocabulary and construction. Many expert evaluators decry the absence of consensual and reliable evaluation tools. The authors present the results of an evaluation of 58 existing guidelines in 4 major health science fields (medicine and epidemiology; nursing and health education; social sciences and public health; psychology / psychiatry, research methods and organization) by expert users (article reviewers, experts allocating funds, editors, etc.). The results propose a toolbox containing 12 consensual criteria with the definitions given by expert users. They also indicate in which disciplinary field each type of criteria is known to be more or less essential. Nevertheless, the authors highlight the limitations of the criteria comparability, as soon as one focuses on their specific definitions. They conclude that each criterion in the toolbox must be explained to come to broader consensus and identify definitions that are consensual to all the fields examined and easily operational.

On making causal claims: A review and recommendations

Social scientists often estimate models from correlational data, where the independent variable has not been exogenously manipulated; they also make implicit or explicit causal claims based on these models. When can these claims be made? We answer this question by first discussing design and estimation conditions under which model estimates can be interpreted, using the randomized experiment as the gold standard. We show how endogeneity--which includes omitted variables, omitted selection, simultaneity, common methods bias, and measurement error--renders estimates causally uninterpretable. Second, we present methods that allow researchers to test causal claims in situations where randomization is not possible or when causal interpretation is confounded, including fixed-effects panel, sample selection, instrumental variable, regression discontinuity, and difference-in-differences models. Third, we take stock of the methodological rigor with which causal claims are being made in a social sciences discipline by reviewing a representative sample of 110 articles on leadership published in the previous 10 years in top-tier journals. Our key finding is that researchers fail to address at least 66 % and up to 90 % of design and estimation conditions that make causal claims invalid. We conclude by offering 10 suggestions on how to improve non-experimental research.

A conceptual framework to assess the effectiveness of HIV prevention

Aim: The relative effectiveness of different methods of prevention of HIV transmission is a subject of debate that is renewed with the integration of each new method. The relative weight of values and evidence in decision-making is not always clearly defined. Debate is often confused, as the proponents of different approaches address the issue at different levels of implementation. This paper defines and delineates the successive levels of analysis of effectiveness, and proposes a conceptual framework to clarify debate. Method / Issue: Initially inspired from work on contraceptive effectiveness, a first version of the conceptual framework was published in 1993 with definition of the Condom Effectiveness Matrix (Spencer, 1993). The framework has since integrated and further developed thinking around distinctions made between efficacy and effectiveness and has been applied to HIV prevention in general. Three levels are defined: theoretical effectiveness (ThE), use-effectiveness (UseE) and population use-effectiveness (PopUseE). For example, abstinence and faithfulness, as proposed in the ABC strategy, have relatively high theoretical effectiveness but relatively low effectiveness at subsequent levels of implementation. The reverse is true of circumcision. Each level is associated with specific forms of scientific enquiry and associated research questions: basic and clinical sciences with ThE; clinical and social sciences with UseE; epidemiology and social, economic and political sciences with PopUseE. Similarly, the focus of investigation moves from biological organisms, to the individual at the physiological and then psychological, social and ecological level, and finally takes as perspective populations and societies as a whole. The framework may be applied to analyse issues on any approach. Hence, regarding consideration of HIV treatment as a means of prevention, examples of issues at each level would be: ThE: achieving adequate viral suppression and non-transmission to partners; UseE: facility and degree of adherence to treatment and medical follow-up; PopUseE: perceived validity of strategy, feasibility of achieving adequate population coverage. Discussion: Use of the framework clarifies the questions that need to be addressed at all levels in order to improve effectiveness. Furthermore, the interconnectedness and complementary nature of research from the different scientific disciplines and the relative contribution of each become apparent. The proposed framework could bring greater rationality to the prevention effectiveness debate and facilitate communication between stakeholders.

How central and connected am I in my family? Bridging and bonding social capital in family configurations of young adults with psychiatric disorders

AIMS: This article explores the structures of relational resources that individuals with psychiatric disorders get from their family configurations using the concept of social capital. METHODS: The research is based on a sample of 54 individuals with psychiatric disorders and behavioural problems, and a comparison sample of 54 individuals without a clinical record matched to the clinical respondents for age and sex. Standard measures of social capital from social network methods are applied on family configurations of individuals from both samples. Differences are tested by variance analysis. RESULTS: Structures of family resources available to individuals with psychiatric disorders are distinct. Individuals with psychiatric disorders perceive themselves as less central in their family configurations and less connected to their family members. Their significant family members are perceived as less connected with each other. As a whole, their family configurations are smaller and do not include spouses or partners. Therefore bridging and bonding social capitals are not readily available for them. CONCLUSION: As family configurations of individuals with psychiatric disorders provide fewer relational resources than other families, they are not able to deal with social integration of individuals with psychiatric disorders on their own.

Structural Analysis of Networks

Network analysis naturally relies on graph theory and, more particularly, on the use of node and edge metrics to identify the salient properties in graphs. When building visual maps of networks, these metrics are turned into useful visual cues or are used interactively to filter out parts of a graph while querying it, for instance. Over the years, analysts from different application domains have designed metrics to serve specific needs. Network science is an inherently cross-disciplinary field, which leads to the publication of metrics with similar goals; different names and descriptions of their analytics often mask the similarity between two metrics that originated in different fields. Here, we study a set of graph metrics and compare their relative values and behaviors in an effort to survey their potential contributions to the spatial analysis of networks.

Multiple imputations applied to the DREAM3 phosphoproteomics challenge: a winning strategy.

DREAM is an initiative that allows researchers to assess how well their methods or approaches can describe and predict networks of interacting molecules [1]. Each year, recently acquired datasets are released to predictors ahead of publication. Researchers typically have about three months to predict the masked data or network of interactions, using any predictive method. Predictions are assessed prior to an annual conference where the best predictions are unveiled and discussed. Here we present the strategy we used to make a winning prediction for the DREAM3 phosphoproteomics challenge. We used Amelia II, a multiple imputation software method developed by Gary King, James Honaker and Matthew Blackwell[2] in the context of social sciences to predict the 476 out of 4624 measurements that had been masked for the challenge. To chose the best possible multiple imputation parameters to apply for the challenge, we evaluated how transforming the data and varying the imputation parameters affected the ability to predict additionally masked data. We discuss the accuracy of our findings and show that multiple imputations applied to this dataset is a powerful method to accurately estimate the missing data. We postulate that multiple imputations methods might become an integral part of experimental design as a mean to achieve cost savings in experimental design or to increase the quantity of samples that could be handled for a given cost.

Theory of mind and social functioning in first episode psychosis

There is evidence of associations between social functioning and theory of mind performance and between social functioning and negative symptoms in chronic psychosis. This study investigates these associations in those with first episode psychosis who are unaffected by factors related to long-term mental illness. Our first hypothesis states that there is an association between theory of mind and social functioning. The second hypothesis states that there is no association between symptoms of psychosis and social functioning. Methods. Fifty-two individuals with first episode psychosis were assessed for social functioning, theory of mind ability (using the Hinting test with verbal stimuli and the Visual Cartoon test with pictorial stimuli), and symptoms of psychosis. Multivariable logistic regression was used to examine associations. Results. Social functioning and theory of mind were associated when measured by the Hinting test (OR 1.70, 95% CI 1.08, 2.66), but not with the Visual Cartoon test (ToM jokes OR 0.61, 95% CI 0.15, 2.53). There was no association between social functioning and symptoms (psychotic symptoms; OR 0.95, 95% CI 0.81, 1.12; selected negative symptoms; OR 1.33, 95% CI 0.78, 2.25). Conclusions. Theory of mind assessed by verbal stimuli is associated with social functioning in a population with first episode psychosis. These findings may be related to language disorders in psychosis.