Local polynomial estimation of Poisson intensities in the presence of reporting delays

Summary.  The system for monitoring suicides in Hong Kong has considerable delays in reporting as the cause of death needs to be determined by a coroner's investigation. However, timely estimates of suicide rates are desirable to assist in the formulation of public health policies. This motivated us to develop a non-parametric procedure to estimate the intensity function of a Poisson process in the presence of reporting delays. We give closed form estimators of the Poisson intensity and the delay distribution, conduct simulation studies to evaluate the method proposed and derive their asymptotic properties. The method proposed is applied to estimate the intensity of suicide in Hong Kong.     

Sampling Returns for Realized Variance Calculations: Tick Time or Transaction Time?

This article introduces a new model for transaction prices in the presence of market microstructure noise in order to study the properties of the price process on two different time scales, namely, transaction time where prices are sampled with every transaction and tick time where prices are sampled with every price change. Both sampling schemes have been used in the literature on realized variance, but a formal investigation into their properties has been lacking. Our empirical and theoretical results indicate that the return dynamics in transaction time are very different from those in tick time and the choice of sampling scheme can therefore have an important impact on the properties of realized variance. For RV we find that tick time sampling is superior to transaction time sampling in terms of mean-squared-error, especially when the level of noise, number of ticks, or the arrival frequency of efficient price moves is low. Importantly, we show that while the microstructure noise may appear close to IID in transaction time, in tick time it is highly dependent. As a result, bias correction procedures that rely on the noise being independent, can fail in tick time and are better implemented in transaction time.     

The Impact of Taking Parental Leave on Fathers’ Participation In Childcare And Relationships With Children: Lessons from Sweden

In Sweden, government-mandated paid parental leave has been available to both mothers and fathers since 1974. By 2006, each parent had two non-transferable leave months and nine additional months to share. From the beginning, parental leave was presented as a policy designed to promote gender equality, with women and men having equal opportunities and responsibilities to contribute economically to the family and care for children. Sweden thus provides a unique setting to explore whether social policy can be an important instrument for changing the gender contract. Analysing survey data from 356 fathers working in large private companies, we found that the amount of parental leave days taken had positive effects on several aspects of fathers’ participation in childcare and on their satisfaction with contact with children, controlling for other factors contributing to fathers’ participation in childcare. Our findings suggest that the full potential of Sweden's parental leave policy for degendering the division of labour for childcare will not likely be met until fathers are strongly encouraged by social policy to take a more equal portion of parental leave.     

New imperfect rankings models for ranked set sampling

Ranked set sampling is a sampling approach that leads to improved statistical inference in situations where the units to be sampled can be ranked relative to each other prior to formal measurement. This ranking may be done either by subjective judgment or according to an auxiliary variable, and it need not be completely accurate. In fact, results in the literature have shown that no matter how poor the quality of the ranking, procedures based on ranked set sampling tend to be at least as efficient as procedures based on simple random sampling. However, efforts to quantify the gains in efficiency for ranked set sampling procedures have been hampered by a shortage of available models for imperfect rankings. In this paper, we introduce a new class of models for imperfect rankings, and we provide a rigorous proof that essentially any reasonable model for imperfect rankings is a limit of models in this class. We then describe a specific, easily applied method for selecting an appropriate imperfect rankings model from the class.     

Gay Affirmative Practice: A Model for Social Work Practice with Gay,Lesbian, and Bisexual Youth

Gay affirmative practice has recently been introduced into the social work literature as a culturally sensitive model for working with gay, lesbian, and bisexual (GLB) adults, however, this model has rarely been applied to practice with GLB youth. In this article, the authors review the literature to present the main tenets of gay affirmative practice, outline the challenges that GLB youth face, and delineate the environmental and individual strengths that can be enhanced to promote well-being. The authors then apply the gay affirmative practice model to GLB youth, offering concrete information about the specific knowledge, attitudes, and skills that social workers should acquire to better serve the unique, yet diverse, needs of GLB youth.     

Data skeletons: simultaneous estimation of multiple quantiles for massive streaming datasets with applications to density estimation

We consider the problem of density estimation when the data is in the form of a continuous stream with no fixed length. In this setting, implementations of the usual methods of density estimation such as kernel density estimation are problematic. We propose a method of density estimation for massive datasets that is based upon taking the derivative of a smooth curve that has been fit through a set of quantile estimates. To achieve this, a low-storage, single-pass, sequential method is proposed for simultaneous estimation of multiple quantiles for massive datasets that form the basis of this method of density estimation. For comparison, we also consider a sequential kernel density estimator. The proposed methods are shown through simulation study to perform well and to have several distinct advantages over existing methods.