Stereotyping and the treatment of missing data for drug and alcohol clinical trials

Stigma and stereotyping of marginalized groups often is insidious and shows up in unlikely places, for instance in how clinical trials consider dropouts in treatment research. A surprising number of studies presume that people who do not complete the study protocol relapse and code their data as if they had been observed. There is no good statistical rationale for this treatment of missing data and numerous and more defensible alternative methods are available. We need to be mindful about our attitudes and preconceptions about the people we are intending to help. There is no good reason to continue to support science built on this scientifically indefensible stereotyping, however unintentional

Maze solvers demystified and some other thoughts

There is a growing interest towards implementation of maze solving in spatially-extended physical, chemical and living systems. Several reports of prototypes attracted great publicity, e.g. maze solving with slime mould and epithelial cells, maze navigating droplets. We show that most prototypes utilise one of two phenomena: a shortest path in a maze is a path of the least resistance for fluid and current flow, and a shortest path is a path of the steepest gradient of chemoattractants. We discuss that substrates with so-called maze-solving capabilities simply trace flow currents or chemical diffusion gradients. We illustrate our thoughts with a model of flow and experiments with slime mould. The chapter ends with a discussion of experiments on maze solving with plant roots and leeches which show limitations of the chemical diffusion maze-solving approach.Comment: This is a preliminary version of the chapter to be published in Adamatzky A. (Ed.) Shortest path solvers. From software to wetware. Springer, 201

Causal inference based on counterfactuals

BACKGROUND: The counterfactual or potential outcome model has become increasingly standard for causal inference in epidemiological and medical studies. DISCUSSION: This paper provides an overview on the counterfactual and related approaches. A variety of conceptual as well as practical issues when estimating causal effects are reviewed. These include causal interactions, imperfect experiments, adjustment for confounding, time-varying exposures, competing risks and the probability of causation. It is argued that the counterfactual model of causal effects captures the main aspects of causality in health sciences and relates to many statistical procedures. SUMMARY: Counterfactuals are the basis of causal inference in medicine and epidemiology. Nevertheless, the estimation of counterfactual differences pose several difficulties, primarily in observational studies. These problems, however, reflect fundamental barriers only when learning from observations, and this does not invalidate the counterfactual concept

Your space or mine? : Mapping self in time

Peer reviewedPublisher PD

On Testing Dependence between Time to Failure and Cause of Failure when Causes of Failure Are Missing

The hypothesis of independence between the failure time and the cause of failure is studied by using the conditional probabilities of failure due to a specific cause given that there is no failure up to certain fixed time. In practice, there are situations when the failure times are available for all units but the causes of failures might be missing for some units. We propose tests based on U-statistics to test for independence of the failure time and the cause of failure in the competing risks model when all the causes of failure cannot be observed. The asymptotic distribution is normal in each case. Simulation studies look at power comparisons for the proposed tests for two families of distributions. The one-sided and the two-sided tests based on Kendall type statistic perform exceedingly well in detecting departures from independence

Cellular responses of Candida albicans to phagocytosis and the extracellular activities of neutrophils are critical to counteract carbohydrate starvation, oxidative and nitrosative stress

Acknowledgments We thank Alexander Johnson (yhb1D/D), Karl Kuchler (sodD/D mutants), Janet Quinn (hog1D/D, hog1/cap1D/D, trx1D/D) and Peter Staib (ssu1D/D) for providing mutant strains. We acknowledge helpful discussions with our colleagues from the Microbial Pathogenicity Mechanisms Department, Fungal Septomics and the Microbial Biochemistry and Physiology Research Group at the Hans Kno¨ll Institute (HKI), specially Ilse D. Jacobsen, Duncan Wilson, Sascha Brunke, Lydia Kasper, Franziska Gerwien, Sea´na Duggan, Katrin Haupt, Kerstin Hu¨nniger, and Matthias Brock, as well as from our partners in the FINSysB Network. Author Contributions Conceived and designed the experiments: PM HW IMB AJPB OK BH. Performed the experiments: PM CD HW. Analyzed the data: PM HW IMB AJPB OK BH. Wrote the paper: PM HW OK AJPB BH.Peer reviewedPublisher PD

Behavioral Inhibition as a Risk Factor for the Development of Childhood Anxiety Disorders: A Longitudinal Study

This longitudinal study examined the additive and interactive effects of behavioral inhibition and a wide range of other vulnerability factors in the development of anxiety problems in youths. A sample of 261 children, aged 5 to 8 years, 124 behaviorally inhibited and 137 control children, were followed during a 3-year period. Assessments took place on three occasions to measure children’s level of behavioral inhibition, anxiety disorder symptoms, other psychopathological symptoms, and a number of other vulnerability factors such as insecure attachment, negative parenting styles, adverse life events, and parental anxiety. Results obtained with Structural Equation Modeling indicated that behavioral inhibition primarily acted as a specific risk factor for the development of social anxiety symptoms. Furthermore, the longitudinal model showed additive as well as interactive effects for various vulnerability factors on the development of anxiety symptoms. That is, main effects of anxious rearing and parental trait anxiety were found, whereas behavioral inhibition and attachment had an interactive effect on anxiety symptomatology. Moreover, behavioral inhibition itself was also influenced by some of the vulnerability factors. These results provide support for dynamic, multifactorial models for the etiology of child anxiety problems