On the trimmed mean and minimax-variance L-estimation in Kolmogorov neighbourhoods

We consider the properties of the trimmed mean, as regards minimax-variance L-estimation of a location parameter in a Kolmogorov neighbourhood K() of the normal distribution: We first review some results on the search for an L-minimax estimator in this neighbourhood, i.e. a linear combination of order statistics whose maximum variance in K_t() is a minimum in the class of L-estimators. The natural candidate – the L-estimate which is efficient for that member of K_t,() with minimum Fisher information – is known not to be a saddlepoint solution to the minimax problem. We show here that it is not a solution at all. We do this by showing that a smaller maximum variance is attained by an appropriately trimmed mean. We argue that this trimmed mean, as well as being computationally simple – much simpler than the efficient L-estimate referred to above, and simpler than the minimax M- and R-estimators – is at least “nearly” minimax.     

Cybersex: The Impact of a Contemporary Problem on the Practices of Marriage and Family Therapists

The number of people accessing the Internet for sexual purposes (cybersex) has increased dramatically over the last 10 years. However, little research has been conducted to determine how frequently clients present for treatment with cybersex‐related issues. One hundred sixty‐four clinical members of the American Association for Marriage and Family Therapy participated in the current study, which was conducted to identify the impacts of cybersex on MFTs’ practices. Most respondents report seeing clients with cybersex‐related issues, with client numbers increasing over the past 2 years. Although most respondents felt prepared to diagnose and treat adults with cybersex problems, half felt unprepared to diagnose and treat children. Lastly, most respondents reported that their required college courses were not helpful in preparing them to diagnose and treat cybersex‐related problems. The implications of study findings are discussed.     

New balanced sampling plans excluding adjacent units

Hedayat et al. [1988a. Sampling plans excluding contiguous units. J. Statist. Plann. Inference 19, 159–170; 1988b. Designs in survey sampling avoiding contiguous units. In: Krishnaiah, P.R., Rao, C.R. (Eds.). Handbook of Statistics, vol. 6. Elsevier, Amsterdam, pp. 575–583] first introduced balanced sampling designs for the exclusion of contiguous units. Sampling plans that excluded the selection of contiguous units within a given sample, while maintaining a constant second-order inclusion probability for non-contiguous units, were investigated for finite populations of N units arranged in a circular, one-dimensional ordering. There remain many open questions about the existence of such plans and their extension to plans excluding adjacent units. We present new generation techniques and new balanced sampling plans for the exclusion of adjacent units under finite, one-dimensional, circularly and linearly ordered populations.     

Transformations for Smooth Regression Models with Multiplicative Errors

We consider whether one should transform to estimate nonparametrically a regression curve sampled from data with a constant coefficient of variation, i.e. with multiplicative errors. Kernel-based smoothing methods are used to provide curve estimates from the data both in the original units and after transformation. Comparisons are based on the mean-squared error (MSE) or mean integrated squared error (MISE), calculated in the original units. Even when the data are generated by the simplest multiplicative error model, the asymptotically optimal MSE (or MISE) is surprisingly not always obtained by smoothing transformed data, but in many cases by directly smoothing the original data. Which method is optimal depends on both the regression curve and the distribution of the errors. Data-based procedures which could be useful in choosing between transforming and not transforming a particular data set are discussed. The results are illustrated on simulated and real data.     

Random regression models for human immunodeficiency virus ribonucleic acid data subject to left censoring and informative drop-outs

Objectives in many longitudinal studies of individuals infected with the human immunodeficiency virus (HIV) include the estimation of population average trajectories of HIV ribonucleic acid (RNA) over time and tests for differences in trajectory across subgroups. Special features that are often inherent in the underlying data include a tendency for some HIV RNA levels to be below an assay detection limit, and for individuals with high initial levels or high ranges of change to drop out of the study early because of illness or death. We develop a likelihood for the observed data that incorporates both of these features. Informative drop-outs are handled by means of an approach previously published by Schluchter. Using data from the HIV Epidemiology Research Study, we implement a maximum likelihood procedure to estimate initial HIV RNA levels and slopes within a population, compare these parameters across subgroups of HIV-infected women and illustrate the importance of appropriate treatment of left censoring and informative drop-outs. We also assess model assumptions and consider the prediction of random intercepts and slopes in this setting. The results suggest that marked bias in estimates of fixed effects, variance components and standard errors in the analysis of HIV RNA data might be avoided by the use of methods like those illustrated.     

Themes and Trends of Journal of Family and Economic Issues: A Review of Twenty Years (1988–2007)

This review article examines the progress and impact of the Journal of Family and Economic Issues (JFEI) between 1988–2007. Over the past 20 years, JFEI has become a major journal publishing articles on the relationship between families and economic systems. JFEI contributed to both the economic and family studies disciplines by publishing articles that explore the interface of these two disciplines. Between 1988 and 2007, JFEI published articles on a variety of themes not often found in other economic or family studies journals such as family resource management, consumer attitudes and behaviors, and economic issues and family relationships. Other unique characteristics of JFEI include many collaborative multidisciplinary studies and many studies analyzing international or cross-cultural samples.     

Adaptive Strategies,Gender Ideology,and Work‐Family Balance Among Dutch Dual Earners

Using questionnaire data on 149 Dutch dual‐earner couples with young children participating in the European Famwork study, we examine how adaptive strategies and gender ideology relate to parents’ perceived success in balancing work and family. Path analysis indicates that some adaptive strategies may harm individuals’ work‐family balance, particularly when they are made in the domain where the time budget is limited. In the need to succeed in multiple roles, however, endorsement of traits traditionally linked with the opposite gender, that is masculine traits for women and feminine traits for men, seems beneficial. We speculate that two underlying mechanisms — social pressure and time constraints — jointly operate in determining perceived success in balancing work and family.     

Futures forecasting for strategic planning at general electric

Without in any way denying that there are forces for stability, I want to state, as strongly as I can, my conviction that change is now more rapid, more complex and more pervasive than ever before in human history. There are forces loose in the world, particularly in the ‘post-industrial society’ of the United States, that go far beyond the youth movement in creating change. As a result, it is utterly unrealistic to pretend that business can continue to plan its strategies in the traditional mode.