Robust estimation methods for exponential data: a monte-carlo comparison

We compare the performance of seven robust estimators for the parameter of an exponential distribution. These include the debiased median and two optimally-weighted one-sided trimmed means. We also introduce four new estimators: the Transform, Bayes, Scaled and Bicube estimators. We make the Monte Carlo comparisons for three sample sizes and six situations. We evaluate the comparisons in terms of a new performance measure, Mean Absolute Differential Error (MADE), and a premium/protection interpretation of MADE. We organize the comparisons to enhance statistical power by making maximal use of common random deviates. The Transform estimator provides the best performance as judged by MADE. The singly-trimmed mean and Transform method define the efficient frontier of premium/protection.     

Testing Variability in the Two-Sample Case

A number of robust methods for testing variability have been reported in previous literature. An examination of these procedures for a wide variety of populations confirms their general robustness. Shoemaker's improvement of the F test extends that test use to a realistic variety of population shapes. However, a combination of the Brown–Forsythe and O'Brien methods based on testing kurtosis is shown to be conservative for a wide range of sample sizes and population distributions. The composite test is also shown to be more powerful in most conditions than other conservative procedures.     

Compulsory income management: Combatting or compounding the underlying causes of homelessness?

Compulsory Income Management (CIM) is a form of conditional welfare that involves the mandatory quarantining of a portion of welfare recipients’ social security payments. Quarantined funds are accessible via a government-issued debit card, with restrictions surrounding where and on what funds can be spent. Official justifications of CIM have framed these policies as attempts to combat substance abuse and gambling problems, and to thus secure better outcomes for welfare recipients and their families. Central to this narrative has been the argument that welfare quarantining will ensure more money is spent on ‘essentials’, including accommodation. No existing studies, however, have specifically interrogated the impacts of CIM on housing security. This article responds to this gap in the literature by reviewing existing research concerning CIM's impacts and locating this research within broader debates regarding the causes of homelessness and the efficacy of individualised policy interventions. In doing so, it highlights CIM's potential to exacerbate housing insecurity not only through technical issues such as rental transfer failures, but also by contributing to underlying stressors such as economic disadvantage; relationship difficulties, poor health and addiction; and social stigma. The article concludes that – far from addressing the structural causes of homelessness – CIM has enflamed them.     

Recognizing Structural Nonidentifiability: When Experiments Do Not Provide Information About Important Parameters and Misleading Models Can Still Have Great Fit

In the quest to model various phenomena, the foundational importance of parameter identifiability to sound statistical modeling may be less well appreciated than goodness of fit. Identifiability concerns the quality of objective information in data to facilitate estimation of a parameter, while nonidentifiability means there are parameters in a model about which the data provide little or no information. In purely empirical models where parsimonious good fit is the chief concern, nonidentifiability (or parameter redundancy) implies overparameterization of the model. In contrast, nonidentifiability implies underinformativeness of available data in mechanistically derived models where parameters are interpreted as having strong practical meaning. This study explores illustrative examples of structural nonidentifiability and its implications using mechanistically derived models (for repeated presence/absence analyses and dose–response of Escherichia coli O157:H7 and norovirus) drawn from quantitative microbial risk assessment. Following algebraic proof of nonidentifiability in these examples, profile likelihood analysis and Bayesian Markov Chain Monte Carlo with uniform priors are illustrated as tools to help detect model parameters that are not strongly identifiable. It is shown that identifiability should be considered during experimental design and ethics approval to ensure generated data can yield strong objective information about all mechanistic parameters of interest. When Bayesian methods are applied to a nonidentifiable model, the subjective prior effectively fabricates information about any parameters about which the data carry no objective information. Finally, structural nonidentifiability can lead to spurious models that fit data well but can yield severely flawed inferences and predictions when they are interpreted or used inappropriately.     

Rank aggregation using latent-scale distance-based models

Rank aggregation aims at combining rankings of a set of items assigned by a sample of rankers to generate a consensus ranking. A typical solution is to adopt a distance-based approach to minimize the sum of the distances to the observed rankings. However, this simple sum may not be appropriate when the quality of rankers varies. This happens when rankers with different backgrounds may have different cognitive levels of examining the items. In this paper, we develop a new distance-based model by allowing different weights for different rankers. Under this model, the weight associated with a ranker is used to measure his/her cognitive level of ranking of the items, and these weights are unobserved and exponentially distributed. Maximum likelihood method is used for model estimation. Extensions to the cases of incomplete rankings and mixture modeling are also discussed. Empirical applications demonstrate that the proposed model produces better rank aggregation than those generated by Borda and the unweighted distance-based models.

     

Reflections of an ordinary life

Philip Anderson (not his real name) was one of thirty people who talked to Wendy Booth and Tim Booth as part of their recently published study Growing Up with Parents who have Learning Difficulties (London: Routledge, 1998). Philip's stoy illustrates many of the themes common to the experience of this group: resilience in the face of risk; the importance of family, especially grandma; social exclusion; the effects of hardship; and the enduring nature of parent-child bonds.     

Internal Migration and Urban Change in Poland

The paper investigates population change and migration over the period 1984–1994 for communes. There are important conclusions emerging from this study. The first is that we are watching now a profound change of population redistribution patterns in Poland. We observed that direct upwards hierarchical mobility has been markedly modified. The first modification is the substantial reduction of migration from rural to urban locations. There were important changes in the role of cities and towns. Largest cities, massive gainers of the seventies and eighties, have tended to lose population in the mid-nineties. It is likely that they lose population mainly to the neighbouring communes. We believe that a suburbanization process has been put into motion. Medium to large sized towns and cities, in the range between 50,000 and 500,000 as well as small, but not the smallest, towns attract substantial parts of the migration pool.     

The Elementary Forms of Place and Their Transformations: A Durkheimian Model

Due to the fragmentary nature of research findings and conceptual models, the Durkheimian legacy remains undervalued in contemporary spatial theory. The paper addresses this neglect by proposing a unified Durkheimian model of place which can be applied to case history and comparative analyses. It draws together the fragmented insights of Durkheimian theory to characterize four elementary forms of place: sacred, profane, liminal and mundane. These place/space identities are maintained and transformed through rituals and narratives which depend upon contingent human actions for their sustenance. The paper concludes with an extended case study which deploys the model to explain the changing meanings of the site of the Bastille (Paris, France) over the past two centuries.     

Using Mand Training to Establish an Echoic Repertoire in Young Children with Autism

The Analysis of Verbal Behavior - This research describes a method that initially establishes a mand repertoire as the first component in producing echoic and tact repertoires in young children...