Statistical shape modeling of pathological scoliotic vertebrae: A comparative analysis

Statistical shape models (SSMs) have been used widely as a basis for segmenting and interpreting complex anatomical structures. The robustness of these models are sensitive to the registration procedures, i.e., establishment of a dense correspondence across a training data set. In this work, two SSMs based on the same training data set of scoliotic vertebrae, and registration procedures were compared. The first model was constructed based on the original binary masks without applying any image pre- and post-processing, and the second was obtained by means of a feature preserving smoothing method applied to the original training data set, followed by a standard rasterization algorithm. The accuracies of the correspondences were assessed quantitatively by means of the maximum of the mean minimum distance (MMMD) and Hausdorf distance (H(D)). Anatomical validity of the models were quantified by means of three different criteria, i.e., compactness, specificity, and model generalization ability. The objective of this study was to compare quasi-identical models based on standard metrics. Preliminary results suggest that the MMMD distance and eigenvalues are not sensitive metrics for evaluating the performance and robustness of SSMs.

K(L) --> pi0 e+ e- and K(L) --> pi0 mu+ mu-: A binary star on the stage of flavor physics

A systematic analysis of New Physics impacts on the rare decays KL→π0ell+ell- is performed. Thanks to their different sensitivities to flavor-changing local effective interactions, these two modes could provide valuable information on the nature of the possible New Physics at play. In particular, a combined measurement of both modes could disentangle scalar/pseudoscalar from vector or axial-vector contributions. For the latter, model-independent bounds are derived. Finally, the KL→π0μ+μ- forward-backward CP-asymmetry is considered, and shown to give interesting complementary information.

A modified test for small-study effects in meta-analyses of controlled trials with binary endpoints

Publication bias and related bias in meta-analysis is often examined by visually checking for asymmetry in funnel plots of treatment effect against its standard error. Formal statistical tests of funnel plot asymmetry have been proposed, but when applied to binary outcome data these can give false-positive rates that are higher than the nominal level in some situations (large treatment effects, or few events per trial, or all trials of similar sizes). We develop a modified linear regression test for funnel plot asymmetry based on the efficient score and its variance, Fisher's information. The performance of this test is compared to the other proposed tests in simulation analyses based on the characteristics of published controlled trials. When there is little or no between-trial heterogeneity, this modified test has a false-positive rate close to the nominal level while maintaining similar power to the original linear regression test ('Egger' test). When the degree of between-trial heterogeneity is large, none of the tests that have been proposed has uniformly good properties.

On Graphically Checking Goodness-of-fit of Binary Logistic Regression Models

OBJECTIVES: This paper is concerned with checking goodness-of-fit of binary logistic regression models. For the practitioners of data analysis, the broad classes of procedures for checking goodness-of-fit available in the literature are described. The challenges of model checking in the context of binary logistic regression are reviewed. As a viable solution, a simple graphical procedure for checking goodness-of-fit is proposed. METHODS: The graphical procedure proposed relies on pieces of information available from any logistic analysis; the focus is on combining and presenting these in an informative way. RESULTS: The information gained using this approach is presented with three examples. In the discussion, the proposed method is put into context and compared with other graphical procedures for checking goodness-of-fit of binary logistic models available in the literature. CONCLUSION: A simple graphical method can significantly improve the understanding of any logistic regression analysis and help to prevent faulty conclusions.

Immunogenomic analysis of insect bite hypersensitivity in a model horse population.

Equine insect bite hypersensitivity (IBH) is a seasonal IgE-mediated dermatosis caused by bites of insects of the genus Culicoides. A familial predisposition for the disease has been shown but, except for the MHC, the genes involved have not been identified so far. An immunogenomic analysis of IBH was performed in a model population of Old Kladruby horses, all living in the same environment. Clinical signs of IBH were used as phenotypic manifestation of IBH. Furthermore, total serum IgE levels were determined in the sera of these horses and used as an independent phenotypic marker for the immunogenetic analysis. Single nucleotide polymorphisms (SNPs) in candidate immunity-related genes were used for association analyses. Genotypes composed of two to five genes encoding interferon gamma -IFNG, transforming growth factor beta 1 -TGFB1, Janus kinase 2 -JAK2, thymic stromal lymphopoietin -TSLP, and involucrin -IVL were associated with IBH, indicating a role of the genes in the pathogenesis of IBH. These findings were supported by analysis of gene expression in skin biopsies of 15 affected and 15 unaffected horses. Two markers associated with IBH, IFNG and TGFB1, showed differences in mRNA expression in skin biopsies from IBH-affected and non-affected horses (p<0.05). Expression of the gene coding for the CD14 receptor molecule -CD14 was different in skin biopsies at p<0.06. When total IgE levels were treated as binary traits, genotypes of IGHE, ELA-DRA, and IL10/b were associated with this trait. When treated as a continuous trait, total IgE levels were associated with genes IGHE, FCER1A, IL4, IL4R, IL10, IL1RA, and JAK2. This first report on non-MHC genes associated with IBH in horses is thus supported by differences in expression of genes known to play a role in allergy and immunity.

Sparse computation for large-scale binary classification

Well-known data mining algorithms rely on inputs in the form of pairwise similarities between objects. For large datasets it is computationally impossible to perform all pairwise comparisons. We therefore propose a novel approach that uses approximate Principal Component Analysis to efficiently identify groups of similar objects. The effectiveness of the approach is demonstrated in the context of binary classification using the supervised normalized cut as a classifier. For large datasets from the UCI repository, the approach significantly improves run times with minimal loss in accuracy.

Reversal of gender differences in Educational Attainment – historical analysis of the West German Case

Background information: During the late 1970s and the early 1980s, West Germany witnessed a reversal of gender differences in educational attainment, as females began to outperform males. Purpose: The main objective was to analyse which processes were behind the reversal of gender differences in educational attainment after 1945. The theoretical reflections and empirical evidence presented for the US context by DiPrete and Buchmann (Gender-specific trends in the value of education and the emerging gender gap in college completion, Demography 43: 1–24, 2006) and Buchmann, DiPrete, and McDaniel (Gender inequalities in education, Annual Review of Sociology 34: 319–37, 2008) are considered and applied to the West German context. It is suggested that the reversal of gender differences is a consequence of the change in female educational decisions, which are mainly related to labour market opportunities and not, as sometimes assumed, a consequence of a ‘boy’s crisis’. Sample: Several databases, such as the German General Social Survey, the German Socio-economic Panel and the German Life History Study, are employed for the longitudinal analysis of the educational and occupational careers of birth cohorts born in the twentieth century. Design and methods: Changing patterns of eligibility for university studies are analysed for successive birth cohorts and gender. Binary logistic regressions are employed for the statistical modelling of the individuals’ achievement, educational decision and likelihood for social mobility – reporting average marginal effects (AME). Results: The empirical results suggest that women’s better school achievement being constant across cohorts does not contribute to the explanation of the reversal of gender differences in higher education attainment, but the increase of benefits for higher education explains the changing educational decisions of women regarding their transition to higher education. Conclusions: The outperformance of females compared with males in higher education might have been initialised by several social changes, including the expansion of public employment, the growing demand for highly qualified female workers in welfare and service areas, the increasing returns of women’s increased education and training, and the improved opportunities for combining family and work outside the home. The historical data show that, in terms of (married) women’s increased labour market opportunities and female life-cycle labour force participation, the raising rates of women’s enrolment in higher education were – among other reasons – partly explained by their rising access to service class positions across birth cohorts, and the rise of their educational returns in terms of wages and long-term employment.

Why Do Some Water Utilities Recycle More than Others? A Qualitative Comparative Analysis in New South Wales, Australia

Although the recycling of municipal wastewater can play an important role in water supply security and ecosystem protection, the percentage of wastewater recycled is generally low and strikingly variable. Previous research has employed detailed case studies to examine the factors that contribute to recycling success but usually lacks a comparative perspective across cases. In this study, 25 water utilities in New South Wales, Australia, were compared using fuzzy-set Qualitative Comparative Analysis (fsQCA). This research method applies binary logic and set theory to identify the minimal combinations of conditions that are necessary and/or sufficient for an outcome to occur within the set of cases analyzed. The influence of six factors (rainfall, population density, coastal or inland location, proximity to users; cost recovery and revenue for water supply services) was examined for two outcomes, agricultural use and "heavy" (i.e., commercial/municipal/industrial) use. Each outcome was explained by two different pathways, illustrating that different combinations of conditions are associated with the same outcome. Generally, while economic factors are crucial for heavy use, factors relating to water stress and geographical proximity matter most for agricultural reuse. These results suggest that policies to promote wastewater reuse may be most effective if they target uses that are most feasible for utilities and correspond to the local context. This work also makes a methodological contribution through illustrating the potential utility of fsQCA for understanding the complex drivers of performance in water recycling.