New recursive estimators of the time-average variance constant

Estimation of the time-average variance constant (TAVC) of a stationary process plays a fundamental role in statistical inference for the mean of a stochastic process. Wu (2009) proposed an efficient algorithm to recursively compute the TAVC with \(O(1)\) memory and computational complexity. In this paper, we propose two new recursive TAVC estimators that can compute TAVC estimate with \(O(1)\) computational complexity. One of them is uniformly better than Wu’s estimator in terms of asymptotic mean squared error (MSE) at a cost of slightly higher memory complexity. The other preserves the \(O(1)\) memory complexity and is better then Wu’s estimator in most situations. Moreover, the first estimator is nearly optimal in the sense that its asymptotic MSE is \(2^{10/3}3^{-2} \fallingdotseq 1.12\) times that of the optimal off-line TAVC estimator.     

Approximate Bayesian computation with composite score functions

Both approximate Bayesian computation (ABC) and composite likelihood methods are useful for Bayesian and frequentist inference, respectively, when the likelihood function is intractable. We propose to use composite likelihood score functions as summary statistics in ABC in order to obtain accurate approximations to the posterior distribution. This is motivated by the use of the score function of the full likelihood, and extended to general unbiased estimating functions in complex models. Moreover, we show that if the composite score is suitably standardised, the resulting ABC procedure is invariant to reparameterisations and automatically adjusts the curvature of the composite likelihood, and of the corresponding posterior distribution. The method is illustrated through examples with simulated data, and an application to modelling of spatial extreme rainfall data is discussed.     

Computing the log concave NPMLE for interval censored data

In analyzing interval censored data, a non-parametric estimator is often desired due to difficulties in assessing model fits. Because of this, the non-parametric maximum likelihood estimator (NPMLE) is often the default estimator. However, the estimates for values of interest of the survival function, such as the quantiles, have very large standard errors due to the jagged form of the estimator. By forcing the estimator to be constrained to the class of log concave functions, the estimator is ensured to have a smooth survival estimate which has much better operating characteristics than the unconstrained NPMLE, without needing to specify a parametric family or smoothing parameter. In this paper, we first prove that the likelihood can be maximized under a finite set of parameters under mild conditions, although the log likelihood function is not strictly concave. We then present an efficient algorithm for computing a local maximum of the likelihood function. Using our fast new algorithm, we present evidence from simulated current status data suggesting that the rate of convergence of the log-concave estimator is faster (between \(n^{2/5}\) and \(n^{1/2}\)) than the unconstrained NPMLE (between \(n^{1/3}\) and \(n^{1/2}\)).     

Variable selection for survival data with a class of adaptive elastic net techniques

The accelerated failure time (AFT) models have proved useful in many contexts, though heavy censoring (as for example in cancer survival) and high dimensionality (as for example in microarray data) cause difficulties for model fitting and model selection. We propose new approaches to variable selection for censored data, based on AFT models optimized using regularized weighted least squares. The regularized technique uses a mixture of \(\ell _1\) and \(\ell _2\) norm penalties under two proposed elastic net type approaches. One is the adaptive elastic net and the other is weighted elastic net. The approaches extend the original approaches proposed by Ghosh (Adaptive elastic net: an improvement of elastic net to achieve oracle properties, Technical Reports 2007) and Hong and Zhang (Math Model Nat Phenom 5(3):115–133 2010), respectively. We also extend the two proposed approaches by adding censoring observations as constraints into their model optimization frameworks. The approaches are evaluated on microarray and by simulation. We compare the performance of these approaches with six other variable selection techniques-three are generally used for censored data and the other three are correlation-based greedy methods used for high-dimensional data.     

Eminent Social Scientists’ Views on Immigration Issues: 1985 and 2006

Following up on a research note by Stephen Moore published in 1985, this article compares the results of the survey conducted in 1985 against one carried out in 2006 on the views of eminent social scientists (economists, political scientists, psychologists, sociologists, historians and anthropologists) on immigration issues. Specifically, the surveys report on whether the respondents are likely to favor an increase in the number of immigrants who are allowed into the United States and other issues such as whether immigrants improve the economy.

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“Grace Is Deceitful and Beauty Is Vain”: How Hassidic Women Cope with the Requirement of Shaving One’s Head and Wearing a Black Kerchief

Women’s modesty norms are often perceived as governing women’s bodies and as patriarchal oppression. This study challenges these perspectives, offering a deeper, multi-dimensional picture showing that the reality of the women’s life is much more complicated. The article chose to discuss aspects of modesty among women of one of the most extreme Jewish ultra-Orthodox groups, and in particular, to investigate how they experience an extremely demanding requirement—shaving off the hair on their head upon marriage and covering their head with a black kerchief. The findings show that there are a variety of voices among the women, ranging from the view that these practices are desirable, through the view that they empower the women, to the view that they damage one’s attractiveness and are quite painful.

Educated Caring: The Emergence of Professional Identity Among Nurses

This article examines the formation of occupational identity in a nursing program. The normative and ideological dimensions of this process are revealed in the program’s goals and the views of educators and students through qualitative data from observations and 30 in-depth interviews. Educators seek to socialize students toward professionalism to raise the occupation’s status by emphasizing the scientific and technical basis of nursing. Yet students uphold a gendered discourse by identifying a normative dimension of caring as central to their occupational identity. The dilemma between professionalism and caring is reconciled as students construct an occupational identity based on “educated caring,” where these two dimensions are equally valuable and significant.

Managing The Lactating Body: The Breast-Feeding Project and Privileged Motherhood

Drawing on interviews with twenty-five mostly white, educated, work-force experienced and class-privileged mothers, this paper explores how these women construct the lactating body as a carefully managed site and breast-feeding as a project—a task to be researched, planned, implemented, and assessed, with reliance on expert knowledge, professional advice, and consumption. The framing of breast-feeding as a project contrasts with the emphases on pleasure, embodied subjectivity, relationality, and empowerment that characterizes much of the recent breast-feeding literature across the humanities and social sciences. I argue that the project frame sheds light on the amount of work and self-discipline involved in compliance with broader middle-class mothering standards set in the consumerist, technological, medicalized, and professionalized contexts that shape parenting in late capitalist America.

Myths of Women and Their Reflection in a Therapy Group

One essential dilemma for modern clinical social work involves the relationship between the processes taking place inside the self and the social, cultural, and political developments affecting a person from the outside. The group-analysis approach focuses on four levels of relationships and communication within the group, among others a primordial level of shared myths, archetypical images, and the collective unconscious as an important component of psychotherapy. This article describes group-analysis therapy with women, analyzing a therapeutic process that used social myths to explore the formative institutionalization processes participants had undergone, thereby expanding themselves, growing, and changing.