Tests of hypotheses based on ranks in the general linear model

A unified approach is developed for testing hypotheses in the general linear model based on the ranks of the residuals. It complements the nonparametric estimation procedures recently reported in the literature. The testing and estimation procedures together provide a robust alternative to least squares. The methods are similar in spirit to least squares so that results are simple to interpret. Hypotheses concerning a subset of specified parameters can be tested, while the remaining parameters are treated as nuisance parameters. Asymptotically, the test statistic is shown to have a chi-square distribution under the null hypothesis. This result is then extended to cover a sequence of contiguous alternatives from which the Pitman efficacy is derived. The general application of the test requires the consistent estimation of a functional of the underlying distribution and one such estimate is furnished.     

Parental Identity and Reflected‐Appraisals: Measurement and Gender Dynamics

A new theoretical model for parental identity, reflected‐appraisals, and behavior was proposed. Parental identity and behavior in married parents were then investigated as a function of partner's and perceived reflected‐appraisals, taking into account gender context effects. Sixty‐four married couples completed the Caregiving and Breadwinning Identity and Reflected‐Appraisal Inventory (CBIRAI), developed for this study to assess parental caregiving and breadwinning identity and reflected‐appraisals, as well as caregiving and breadwinning behavior measures. The model was confirmed for fathers and partially confirmed for mothers. Specifically, caregiving identity and behavior in fathers, and breadwinning identity in mothers were functions of perceived reflected‐appraisals. Limitations and implications are discussed.     

Service robotics: do you know your new companion? Framing an interdisciplinary technology assessment

Service-Robotic—mainly defined as “non-industrial robotics”—is identified as the next economical success story to be expected after robots have been ubiquitously implemented into industrial production lines. Under the heading of service-robotic, we found a widespread area of applications reaching from robotics in agriculture and in the public transportation system to service robots applied in private homes. We propose for our interdisciplinary perspective of technology assessment to take the human user/worker as common focus. In some cases, the user/worker is the effective subject acting by means of and in cooperation with a service robot; in other cases, the user/worker might become a pure object of the respective robotic system, for example, as a patient in a hospital. In this paper, we present a comprehensive interdisciplinary framework, which allows us to scrutinize some of the most relevant applications of service robotics; we propose to combine technical, economical, legal, philosophical/ethical, and psychological perspectives in order to design a thorough and comprehensive expert-based technology assessment. This allows us to understand the potentials as well as the limits and even the threats connected with the ongoing and the planned implementation of service robots into human lifeworld—particularly of those technical systems displaying increasing grades of autonomy.     

Telling a Good Story: Using Narratives in Vocational Rehabilitation With Veterans

Because of the high chronicity of work-related problems in a Veterans Administration Medical Center population, many of the traditional methods of career assessment, counseling, and placement have proven ineffectual. In this article the authors detail the development of an intervention based on narrative or storytelling principles. They describe efforts to introduce this model to patients as well as to relate patients' stories to vocational outcomes. The usefulness of stories as an organizing principle for counselors and clients is discussed, and suggestions are offered for further uses of storytelling interventions.     

Empirical Bayes Small-Area Estimation Using Logistic Regression Models and Summary Statistics

Many of the available methods for estimating small-area parameters are model-based approaches in which auxiliary variables are used to predict the variable of interest. For models that are nonlinear, prediction is not straightforward. MacGibbon and Tomberlin and Farrell, MacGibbon, and Tomberlin have proposed approaches that require microdata for all individuals in a small area. In this article, we develop a method, based on a second-order Taylor-series expansion to obtain model-based predictions, that requires only local-area summary statistics for both continuous and categorical auxiliary variables. The methodology is evaluated using data based on a U.S. Census.