Generalised Rank Regression Estimator with Standard Error Adjusted Lasso

One of the standard variable selection procedures in multiple linear regression is to use a penalisation technique in least‐squares (LS) analysis. In this setting, many different types of penalties have been introduced to achieve variable selection. It is well known that LS analysis is sensitive to outliers, and consequently outliers can present serious problems for the classical variable selection procedures. Since rank‐based procedures have desirable robustness properties compared to LS procedures, we propose a rank‐based adaptive lasso‐type penalised regression estimator and a corresponding variable selection procedure for linear regression models. The proposed estimator and variable selection procedure are robust against outliers in both response and predictor space. Furthermore, since rank regression can yield unstable estimators in the presence of multicollinearity, in order to provide inference that is robust against multicollinearity, we adjust the penalty term in the adaptive lasso function by incorporating the standard errors of the rank estimator. The theoretical properties of the proposed procedures are established and their performances are investigated by means of simulations. Finally, the estimator and variable selection procedure are applied to the Plasma Beta‐Carotene Level data set.     

Stochastic metafrontiers

ABSTRACT

We consider the case of production units arranged into a number of groups. All units within a group choose output–input combinations from the same production possibilities set that is represented by a stochastic frontier model. The metafrontier is the envelope of the group-specific frontiers. We are interested in the metafrontier distance, which is the amount by which the group-specific frontier lies below the metafrontier.

Previous work has measured the metafrontier distance using the deterministic portion of the frontier. In a stochastic frontier model, this is not appropriate. We show how to evaluate the metafrontier distance, and we demonstrate the empirical relevance of this issue.     

Generalized Estimation of the BLUP in Mixed-Effects Models: A Comparison with ML and REML

The Best Linear Unbiased Predictor (BLUP) in mixed models is a function of the variance components and they are estimated using maximum likelihood (ML) or restricted ML methods. Nonconvergence of BLUP would occur due to a drawback of the standard likelihood-based approaches. In such situations, ML and REML either do not provide any BLUPs or all become equal. To overcome this drawback, we provide a generalized estimate (GE) of BLUP that does not suffer from the problem of negative or zero variance components, and compare its performance against the ML and REML estimates of BLUP. Simulated and published data are used to compare BLUP.     

Influential observations in the analysis of variance

The effect of influentia lob servations on t h e parameter estimates of ordinary l e a s t squares regression models has received considerable attentio n fn the last decade. However, very little attention has been given t o the problem of in fluent ia lobserva- tions in the analysis of variance . The purpose of t h i s paper is t o show by way of examples that influential observations can alter the conclusions of tests of hypotheses in the analysis of variance . Regression diagnostics for identif y in g both extreme points and outliers can be used to reveal potential data and design problems.     

Reactions of students to different settings of field experience

The study assessed Israeli students’ emotional–experiential reaction and attitude to different client populations, following a week-long experience in one of five social services settings. The study provides preliminary findings regarding the implications of first year students’ experience on their emphatic skills, a subject that generally has not received adequate scholarly attention. Using a purpose-built, self-administered questionnaire, we found students’ emotional–experiential response to their experience differed by the setting in which they were placed, being lowest in the Bedouin oriented services, intermediate among those placed in juvenile correction services, and highest in mental health, adult and child disability services. Responses were independent of all other explanatory variables, including sex, cognitive ability, previous training experience and perceptual shifts concerning the population served. We discuss possible reasons for these differences.

     

Using conceptual models as a planning and evaluation tool in conservation

Conservation projects are dynamic interventions that occur in complex contexts involving intricate interactions of social, political, economic, cultural, and environmental factors. These factors are constantly changing over time and space as managers learn more about the context within which they work. This complex context poses challenges for planning and evaluating conservation project. In order for conservation managers and evaluation professionals to design good interventions and measure project success, they simultaneously need to embrace and deconstruct contextual complexity.In this article, we describe conceptual models—a tool that helps articulate and make explicit assumptions about a project's context and what a project team hopes to achieve. We provide real-world examples of conceptual models, discuss the relationship between conceptual models and other evaluation tools, and describe various ways that conceptual models serve as a key planning and evaluation tool. These include, for example, that they document assumptions about a project site and they provide a basis for analyzing theories of change.It is impractical to believe that we can completely eliminate detail or dynamic complexity in projects. Nevertheless, conceptual models can help reduce the effects of this complexity by helping us understand it.     

Children's response to the medical visit for allegations of sexual abuse: maternal perceptions and predicting variables

This study examined maternal perceptions of their child's response to the medical evaluation for alleged sexual abuse. A total of 50 mothers were interviewed 6 months after a visit to a Child Protection Clinic for a medical evaluation of alleged sexual abuse. The mothers answered a questionnaire on their child's reactions to the medical visit. More than 60% of children were perceived as being reassured about physical integrity. The degree of psychological distress was independent of perpetrator's identity and severity of the abuse. Mothers considered that a hypothetical second visit would generate in their child a level of anxiety that increased with perceived intensity of fear of the examination and decreased with perceived kindness of the physician. These results suggest that the physician's behaviour during the medical evaluation for alleged sexual abuse has an influence on the child's degree of distress that is independent of type and severity of abuse. Copyright © 2001 John Wiley & Sons, Ltd.     

Fertility decline in Nigeria: the case of Ekpoma Region,Bendel State

Data concerning 624 randomly selected mothers in Ekpoma Region, Nigeria, are used to analyze socioeconomic and cultural determinants of fertility. Factors considered include education, occupation, income, religion, age at first marriage, breast-feeding, and contraceptive practice. The author concludes that the conditions for fertility decline are now in place and that this decline could be accelerated by discouraging early marriage, increasing female education, and promoting contraception.