Nonparametric regression for threshold data

Consider a detector which records the times at which the endogenous variable of a nonparametric regression model exceeds a certain threshold. If the error distribution is known, the regression function can still be identified from these threshold data. The author constructs estimators for the regression function that are transformations of kernel estimators. She determines the bandwidth that minimizes the asymptotic mean average squared error. Her investigation was motivated by recent work on stochastic resonance in neuroscience and signal detection theory, where it was observed that detection of a subthreshold signal is enhanced by the addition of noise. The author compares her model with several others that have been proposed in the recent past.     

Discrete-time survival analysis under ranked set sampling: an application to Turkish motor insurance data

Survival models with continuous-time data are still superior methods of survival analysis. However when the survival data is discrete, taking it as continuous leads the researchers to incorrect results and interpretations. The discrete-time survival model has some advantages in applications such as it can be used for non-proportional hazards, time-varying covariates and tied observations. However, it has a disadvantage about the reconstruction of the survival data and working with big data sets. Actuaries are often rely on complex and big data whereas they have to be quick and efficient for short period analysis. Using the mass always creates inefficient processes and consumes time. Therefore sampling design becomes more and more important in order to get reliable results. In this study, we take into account sampling methods in discrete-time survival model using a real data set on motor insurance. To see the efficiency of the proposed methodology we conducted a simulation study.     

Using social media-based drama therapy and family counselling to treat symptoms of postpartum depression among women

This study examines the impact of social media-based drama therapy and family counselling in reducing symptoms of postpartum depression (PPD) in women aged 18–34. The researchers used a quasi-experimental design and randomly assigned the participants (n = 303) to the control, drama therapy, and family counselling groups. The key findings of the study are as follows. First, at baseline, women not only showed more symptoms of PPD than their male counterparts, but men also reached the PPD threshold of 12/13. Second, the difference between women and men regarding their PPD scores achieved statistical significance (p = 0.004). However, during the post-intervention assessment, men who received drama therapy intervention reported a significant drop in their PPD below the threshold of 12/13. Only women whose spouses received family counselling on spousal support reported a significant drop in their PPD. However, those whose partners did not receive family counselling on spousal support still reported PPD scores within the threshold. In both instances, women in the control group still had high PPD scores. Finally, during the 6-month follow-up assessment, even men in the control group did not have significant symptoms of PPD as their scores dropped below the threshold. On the contrary, women in the control group still had high PPD, indicating that PPD lasted more in women than in men. Also, women whose husbands received family counselling on spousal support reported PPD scores below the threshold. However, women whose husbands did not receive spousal counselling still had PPD scores at the threshold, even though their scores marginally dropped.