ROBUST ESTIMATION OF SMALL‐AREA MEANS AND QUANTILES

Small‐area estimation techniques have typically relied on plug‐in estimation based on models containing random area effects. More recently, regression M‐quantiles have been suggested for this purpose, thus avoiding conventional Gaussian assumptions, as well as problems associated with the specification of random effects. However, the plug‐in M‐quantile estimator for the small‐area mean can be shown to be the expected value of this mean with respect to a generally biased estimator of the small‐area cumulative distribution function of the characteristic of interest. To correct this problem, we propose a general framework for robust small‐area estimation, based on representing a small‐area estimator as a functional of a predictor of this small‐area cumulative distribution function. Key advantages of this framework are that it naturally leads to integrated estimation of small‐area means and quantiles and is not restricted to M‐quantile models. We also discuss mean squared error estimation for the resulting estimators, and demonstrate the advantages of our approach through model‐based and design‐based simulations, with the latter using economic data collected in an Australian farm survey.     

The narrative self in autobiographical accounts of illness

The paper analyzes autobiographical acounts of the experience of chronic illness and its treatment to develop a sociological theory of the self. It is suggested that ‘self’ is not a biologistic or psycologistic thing. Rather self is autobiographical narrative – hence the narrative self. It is argued that four elements constitute such narrative selves in autobiographical discourse: evaluative relationships between events in time; cosmology; power relationships; and conceptualisation of self as object.     

The impact of involuntary job loss on those disabled by society: a pilot study to encourage effective participation

Over half of the people who become disabled whilst employed are thought to be pressured into leaving their job. This study investigates the experience of involuntary retirement/redundancy due to disability. Three researchers who had all experienced such involuntary job loss were trained to conduct the research. Semi-structured interviews were designed and conducted by disabled researchers. The training of the researchers enabled them to successfully conduct a research project. The results of the project show the impact of involuntary job loss due to disability to be considerable. This study would suggest that government reforms to create new opportunities for disabled people of a working age are well overdue. Although there were some problems experienced with the amount of training required and the lack of objectivity, training disabled researchers to conduct research proved to be a valuable experience for both the researchers and the facilitators.     

ESTIMATING DISTRIBUTION FUNCTIONS FROM SURVEY DATA WITH LIMITED BENCHMARK INFORMATION

The model-based approach to estimation of finite population distribution functions introduced in Chambers & Dunstan (1986) is extended to the case where only summary information is available for the auxiliary size variable. Monte Carlo results indicate that this ‘limited information’ extension is almost as efficient as the ‘full information’ method proposed in the above reference. These results also indicate that the model-based confidence intervals generated by either of these methods have superior coverage properties to more conventional design-based confidence intervals.     

Dosage-response analysis for a semi-quantal response derived from an aqueous biological assay

This paper is concerned with the interpretation of semi-quantal or graded responses in biological assay. On the basis of a model by which the various response categories represent contiguous intervals on an underlying quantitative scale reflecting time to death, a method of analysis for semi-quantal data is put forward. The results are illustrated by an aqueous assay designed to assess the toxicity of an effluent. It is confirmed that the proposed method of analysis leads to more precise estimates of the dosage-response relation than the alternative quantal response analysis of each response threshold.     

Statistical Computing: History and Trends

The evolution of computers is currently in a period of rapid change, stimulated by radically cheaper and smaller devices for processing and memory. These changes are certain to provide major opportunities and challenges for the use of computers in statistics. This article looks at history and current trends, in both general computing and statistical computing, with the goal of identifying key features and requirements for the near future. A discussion of the S language developed at Bell Laboratories illustrates some program design principles that can make future work on statistical programs more effective and more valuable.