Summary We describe a model for the analysis of data distributed over irregularly shaped spatial domains with complex boundaries, strong concavities and interior holes. Adopting an approach that is typical of functional data analysis, we propose a spatial spline regression model that is computationally efficient, allows for spatially distributed covariate information and can impose various conditions over the boundaries of the domain. Accurate surface estimation is achieved by the use of piecewise linear and quadratic finite elements.

In recent years, a number of studies have applied generalized additive models to time series data to estimate associations between exposure to air pollution and cardiorespiratory morbidity and mortality. If concurvity, the nonparametric analogue of multicollinearity, is present in the data, statistical software such as S-plus can seriously underestimate the variance of fitted model parameters, leading to significance tests with inflated type 1 error. This paper uses computer simulation and analyses of actual epidemiologic data to explore this underestimation of standard errors. We provide a method for assessing concurvity in data and an alternate class of models that is unaffected by concurvity. We argue that some degree of concurvity is likely to be present in all epidemiologic time series datasets and we explore through the use of meta-analysis the possible impact of concurvity on the existing body of work relating ambient levels of sulfate particles to mortality.

Optimal performance is critical for decision-making tasks from medicine to autonomous driving, however common performance measures may be too general or too specific. For binary classifiers, diagnostic tests or prognosis at a timepoint, measures such as the area under the receiver operating characteristic curve, or the area under the precision recall curve, are too general because they include unrealistic decision thresholds. On the other hand, measures such as accuracy, sensitivity or the F1 score are measures at a single threshold that reflect an individual single probability or predicted risk, rather than a range of individuals or risk. We propose a method in between, deep ROC analysis, that examines groups of probabilities or predicted risks for more insightful analysis. We translate esoteric measures into familiar terms: AUC and the normalized concordant partial AUC are balanced average accuracy (a new finding); the normalized partial AUC is average sensitivity; and the normalized horizontal partial AUC is average specificity. Along with post-test measures, we provide a method that can improve model selection in some cases and provide interpretation and assurance for patients in each risk group. We demonstrate deep ROC analysis in two case studies and provide a toolkit in Python.

Background Sexual desire or frequency problems are exceedingly common, but treatment of them has been less than effective. Aim The goal of this study was to develop a cost-effective, accessible intervention to deal with sexual desire or frequency problems, including sexual desire discrepancy, by enhancing the quality of couples’ erotic intimacy. Methods 45 couples (38 heterosexual and 7 same-sex couples) distressed by sexual desire or frequency problems were seen in a 16-hour, group couples therapy intervention. Participants completed the New Sexual Satisfaction Scale (NSSS) at pretest, posttest, and at 6-month follow-up. Outcomes The NSSS plus 3 additional items at pretest, posttest, and at 6-month follow-up and patients’ written feedback. Results Statistically significant differences were found between pre-tests and post-tests in satisfaction with intensity of sexual arousal; creativity; frequency; sexual functioning; partner's sexual availability; partner's initiation of sexual activity; emotional opening up during sex; positive sexual reactions to the partner; communication of sexual wishes, preferences and desires; and balance between giving and receiving during sex. The largest improvement and effect sizes were found in overall satisfaction with one's sex life from pre-test to post-test and 6-month follow-up. Clinical Implications Low sexual desire or frequency problems can be treated effectively by enhancing the quality of the couple's erotic connection, thereby creating desirable sex. Strengths & Limitations The strengths include the combination of quantitative and qualitative data. Limitations included the small number of same-sex couples. Conclusion Sexual enhancement group couples therapy provides an effective, accessible, and affordable approach to low desire or frequency complaints in distressed couples.