Bayesian Regularisation in Structured Additive Regression Models for Survival Data

During recent years, penalized likelihood approaches have attracted a lot of interest both in the area of semiparametric regression and for the regularization of high-dimensional regression models. In this paper, we introduce a Bayesian formulation that allows to combine both aspects into a joint regression model with a focus on hazard regression for survival times. While Bayesian penalized splines form the basis for estimating nonparametric and flexible time-varying effects, regularization of high-dimensional covariate vectors is based on scale mixture of normals priors. This class of priors allows to keep a (conditional) Gaussian prior for regression coefficients on the predictor stage of the model but introduces suitable mixture distributions for the Gaussian variance to achieve regularization. This scale mixture property allows to device general and adaptive Markov chain Monte Carlo simulation algorithms for fitting a variety of hazard regression models. In particular, unifying algorithms based on iteratively weighted least squares proposals can be employed both for regularization and penalized semiparametric function estimation. Since sampling based estimates do no longer have the variable selection property well-known for the Lasso in frequentist analyses, we additionally consider spike and slab priors that introduce a further mixing stage that allows to separate between influential and redundant parameters. We demonstrate the different shrinkage properties with three simulation settings and apply the methods to the PBC Liver dataset

High-dimensional Structured Additive Regression Models: Bayesian Regularisation, Smoothing and Predictive Performance

Data structures in modern applications frequently combine the necessity of flexible regression techniques such as nonlinear and spatial effects with high-dimensional covariate vectors. While estimation of the former is typically achieved by supplementing the likelihood with a suitable smoothness penalty, the latter are usually assigned shrinkage penalties that enforce sparse models. In this paper, we consider a Bayesian unifying perspective, where conditionally Gaussian priors can be assigned to all types of regression effects. Suitable hyperprior assumptions on the variances of the Gaussian distributions then induce the desired smoothness or sparseness properties. As a major advantage, general Markov chain Monte Carlo simulation algorithms can be developed that allow for the joint estimation of smooth and spatial effects and regularised coefficient vectors. Two applications demonstrate the usefulness of the proposed procedure: A geoadditive regression model for data from the Munich rental guide and an additive probit model for the prediction of consumer credit defaults. In both cases, high-dimensional vectors of categorical covariates will be included in the regression models. The predictive ability of the resulting high-dimensional structure additive regression models compared to expert models will be of particular relevance and will be evaluated on cross-validation test data

Development and Validation of the Single Item Narcissism Scale (SINS)

Main Objectives: The narcissistic personality is characterized by grandiosity, entitlement, and low empathy. This paper describes the development and validation of the Single Item Narcissism Scale (SINS). Although the use of longer instruments is superior in most circumstances, we recommend the SINS in some circumstances (e.g. under serious time constraints, online studies). Methods: In 11 independent studies (total N = 2,250), we demonstrate the SINS\u27 psychometric properties. Results: The SINS is significantly correlated with longer narcissism scales, but uncorrelated with self-esteem. It also has high test-retest reliability. We validate the SINS in a variety of samples (e.g., undergraduates, nationally representative adults), intrapersonal correlates (e.g., positive affect, depression), and interpersonal correlates (e.g., aggression, relationship quality, prosocial behavior). The SINS taps into the more fragile and less desirable components of narcissism. Significance: The SINS can be a useful tool for researchers, especially when it is important to measure narcissism with constraints preventing the use of longer measures

Development and Validation of the Single Item Trait Empathy Scale (SITES)

Empathy involves feeling compassion for others and imagining how they feel. In this article, we develop and validate the Single Item Trait Empathy Scale (SITES), which contains only one item that takes seconds to complete. In seven studies (N = 5724), the SITES was found to be both reliable and valid. It correlated in expected ways with a wide variety of intrapersonal outcomes. For example, it is negatively correlated with narcissism, depression, anxiety, and alexithymia. In contrast, it is positively correlated with other measures of empathy, self-esteem, subjective well-being, and agreeableness. The SITES also correlates with a wide variety of interpersonal outcomes, especially compassion for others and helping others. The SITES is recommended in situations when time or question quantity is constrained

Survey of NCAA Athletic Trainers’ Administration of the National Wrestling Coaches Association Weight Certification Program

Context: The National Collegiate Athletic Association (NCAA) implemented a minimum weight certification program in 1997 to help protect wrestlers from dangerous weight loss practices. Despite nearly a quarter of a century of this program, there is no published research detailing the implementation of it. Objective: Determine how the NCAA minimum weight certification is being implemented across Division I programs. Design: Cross-sectional study Setting: Survey Patients or Other Participants: A total of 35 (45.5%) of 77 NCAA division I wrestling athletic trainers responded to the survey. Main Outcome Measure(s): Survey data on how the NCAA minimum weight certification program was implemented at the division I level was collected. Results: Nearly all respondents used athletic trainers to take their measurements. Most staff (74.3%) had five or more years of experience taking the measurements, and only one (2.9%) had less than a year of experience. The time prior to competition that the measurement was taken ranged widely from 2 to 110 days. Nearly all (97.1%) used skinfold calipers, and just one program (2.9%) specified a different method, iDXA scan. Of those using the skinfold calipers, 52.9% used Lange calipers and 32.4% did not know the caliper type. Everyone used the same three measurement locations. Body density was converted to %BF with the Brozek formula at 13% of the institutions, the Siri formula at 4.3% of programs, “other” (defined by respondents as the optimal performance calculator provided by the NWCA) at 13% of schools, and 69.6% did not know. Conclusion: Overall, there appears to be great consistency in the administration of the minimal wrestling weight standards across NCAA Division I wrestling programs

Empathy, Narcissism, and Visual Arts Engagement

Empathy involves imagining others’ minds and feeling compassion for them, and narcissism is a sense of inflated self-esteem with a low regard for others. In this chapter, I will review scientific research on empathy, narcissism, and visual arts, including creativity. I will present evidence that there are two paths to arts engagement, just as with any behavior. Some people likely get involved with the arts because they care about others and want to improve the world in some way, and some people get involved for more self-focused reasons. The final section will make recommendations for future research and for how these ideas can be applied to museum settings

Positive Technology: Using Mobile Phones for Psychosocial Interventions

This chapter reviews the use of mobile phones in psychosocial interventions. Specifically, it reviews research studies that have used text messages (SMS) or smartphone applications (apps) to improve people’s mental health, psychological well-being, or social relationships. Psychosocial interventions are emerging from the larger and more established mobile health (mHealth) literature of physical health interventions. The scientific knowledge of psychosocial interventions is currently quite limited, with only a few published large randomized control trials. Most of those are limited to North American or European participant samples. The advantages and disadvantages of mobile interventions are discussed, along with recommendations for best practices. The success of future research is dependent upon more researcher-friendly tools to implement interventions