An exploratory study of different approaches between social work practice and correctional services in Hong Kong Special Administrative Region

This paper tries to explore the differences between social work and correctional services from the aspects of professional boundaries, concept, content, construct, context, approach, function, professional identity and relationship with service users. Through these, social workers will be informed what are the limitations of their service in a correctional environment, whilst for correctional officers, a better understanding of the philosophical stance of social services which may be helpful for them in discharging their dual role of law enforcer and social worker under the contemporary correctional policy stressing rehabilitation and reintegration of offenders.     

A Note on Local Influence Based on Normal Curvature

Object functions other than the likelihood displacement, such as a parameter estimate or a test statistic, can also be used in local influence analysis. The normal curvatures of these object functions have been studied in situations where the slopes were non-zero. In these situations, we show that the normal curvature is not scale invariant and thus ambiguous conclusions will be drawn. Comments on the application of the general normal curvature formula are presented.     

Tests for Trend in Developmental Toxicity Experiments with Correlated Binary Data

In this article, the operating characteristics of recently proposed tests for trend in correlated binary data arising in laboratory studies of developmental toxicity are examined using both computer-generated and experimental data. Specifically, we consider adjusted Cochran-Armitgc tests based on the Rao-Scott transformation which are of the same general form as that for uncorrelated data. In addition, generalized score tests based on generalized estimating equations allowing for extra-binomial variation in the data are discussed. Specific forms of these statistics demonstrating favorable type I and type II error rates are identified and recommended for use in practice. The application of these tests is illustrated using data from studies of developmental toxicity that have been reported in the literature.     

On the robust two wided tolerance limits based on MML estimators

Recently, Balakrishnan and Kocherlakota (1985) have proposed robust two sided tolerance limits based on the MML estimators. They have simulated the actual γ values attained by their procedure and the classical procedure based on [Xbar] and s. However, there seems to have been an error in their simulation. Here, we present the corrected table of the simulated values of γ which also reverses their recommendations.     

Structural identification and variable selection in high-dimensional varying-coefficient models

Varying-coefficient models have been widely used to investigate the possible time-dependent effects of covariates when the response variable comes from normal distribution. Much progress has been made for inference and variable selection in the framework of such models. However, the identification of model structure, that is how to identify which covariates have time-varying effects and which have fixed effects, remains a challenging and unsolved problem especially when the dimension of covariates is much larger than the sample size. In this article, we consider the structural identification and variable selection problems in varying-coefficient models for high-dimensional data. Using a modified basis expansion approach and group variable selection methods, we propose a unified procedure to simultaneously identify the model structure, select important variables and estimate the coefficient curves. The unique feature of the proposed approach is that we do not have to specify the model structure in advance, therefore, it is more realistic and appropriate for real data analysis. Asymptotic properties of the proposed estimators have been derived under regular conditions. Furthermore, we evaluate the finite sample performance of the proposed methods with Monte Carlo simulation studies and a real data analysis.