Integer-valued autoregressive processes with periodic structure

In this paper the periodic integer-valued autoregressive model of order one with period T, driven by a periodic sequence of independent Poisson-distributed random variables, is studied in some detail. Basic probabilistic and statistical properties of this model are discussed. Moreover, parameter estimation is also addressed. Specifically, the methods of estimation under analysis are the method of moments, least squares-type and likelihood-based ones. Their performance is compared through a simulation study.     

CONVERGENCE AND PREDICTION OF PRINCIPAL COMPONENT SCORES IN HIGH-DIMENSIONAL SETTINGS

A number of settings arise in which it is of interest to predict Principal Component (PC) scores for new observations using data from an initial sample. In this paper, we demonstrate that naive approaches to PC score prediction can be substantially biased towards 0 in the analysis of large matrices. This phenomenon is largely related to known inconsistency results for sample eigenvalues and eigenvectors as both dimensions of the matrix increase. For the spiked eigenvalue model for random matrices, we expand the generality of these results, and propose bias-adjusted PC score prediction. In addition, we compute the asymptotic correlation coefficient between PC scores from sample and population eigenvectors. Simulation and real data examples from the genetics literature show the improved bias and numerical properties of our estimators.     

Mad, Bad, or Reasonable? Newspaper Portrayals of the Battered Woman Who Kills

A heated debate about battered women who kill abusive male partners started in the 1970s. In this study, we tracked the public discourse on battered women who kill by coding 250 newspaper articles published between 1978 and 2002. Using four typifying models, we found that leading explanations for why battered women kill medicalized then criminalized their actions; they were mad then bad. We also found that reporters used quotes from claims makers supporting conventional or medical typifications of battered women to a much greater degree than statements from alternative, feminist sources. In conclusion, simplified, sensational and conventional understandings of crime causation drove the social construction of “the battered woman who kills”. She may be mad or bad, but rarely has she been portrayed as reasonable. Suggestions for promoting feminist narrative in the media are also provided.     

Recovery of inter-block information: extensions in a two variance component model

For a two variance component mixed linear model, it is shown that under suitable conditions there exists a nonlinear unbiased estimator that is better than a best linear unbiased estimator defined with respect to a given singular covariance matrix. It is also shown how this result applies to improving on intra-block estimators and on estimators like the unweighted means estimator in a random one-way model.     

A cumulative ecological–transactional risk model of child maltreatment and behavioral outcomes: Reconceptualizing early maltreatment report as risk factor

The current analysis was designed to critically examine the tendency to focus on child maltreatment as a unique risk factor and test the resulting assumption of a direct causal relationship between early maltreatment and later behavioral problems. The variation seen in behavioral outcomes among children reported for maltreatment early in life led us to hypothesize that the cumulative level of risk facing children and their families can, at least in part, account for that variation in outcome. Participants were 242 mothers of predominantly at-risk newborn infants who were interviewed shortly after giving birth. The State Central Registry of Maltreatment was then reviewed over each child's first four years of life to assess for early maltreatment. Following the neonatal interviews, mothers completed the Child Behavior Checklist when their children were 4, 6, 8, 10 and 12 years-of-age. Although early maltreatment report does appear to be important to early child functioning, the cumulative level of risk more strongly predicts long-term clinical behavioral difficulty. High-risk children who were not reported for maltreatment by age 4 demonstrate greater behavioral problem trajectories than did low-risk children with a maltreatment report. Maltreatment itself may be best conceptualized as an important, but not singularly so, risk factor for later behavioral problems. In focusing directly on reported maltreatment, our child protective systems may be paying too little attention to what else is going wrong in the lives of children and targeting intervention efforts in the wrong direction. When it comes to early maltreatment our child protective policy and practice need to broaden their lenses to include greater emphasis on overall family functioning, stress and well-being. Early maltreatment, it seems, may be a symptom of more profound problems in the early environments of our most vulnerable children, rather than the problem itself.     

Orthodox BLUP versus h-likelihood methods for inferences about random effects in Tweedie mixed models

Recently, the orthodox best linear unbiased predictor (BLUP) method was introduced for inference about random effects in Tweedie mixed models. With the use of h-likelihood, we illustrate that the standard likelihood procedures, developed for inference about fixed unknown parameters, can be used for inference about random effects. We show that the necessary standard error for the prediction interval of the random effect can be computed from the Hessian matrix of the h-likelihood. We also show numerically that the h-likelihood provides a prediction interval that maintains a more precise coverage probability than the BLUP method.     

Learning Clinical Practice by Simulation in Law and Social Work

This paper discusses the development and evaluation of a package that was designed to simulate the Family Court of Australia. The origins of the simulation derive from the problems associated with access to the Family Court as it is a closed court, and the need to examine the relationship between two professions that work in the Family Court. The point of the simulation was to examine the unexpected effects which may not be obvious from simple discussion of the subject. The simulation provided a situation where the less rational aspects of court work could manifest themselves. Law students found many new interpersonal problems when they were confronted with the idiosyncrasies of clients, and trainee counsellors found the intricacies of the law daunting.     

Correlational biases in mean response latency differences

Multifarious psychological constructs are indexed by the mean latency difference (MLD), the within-subject difference between mean response latency on two tasks. Two associations consistently emerge in mean latency data. Firstly, across subjects, mean latencies on distinct tasks are positively correlated. This correlation arises from individual differences in general rates of information processing that are a shared influence on response latency in diverse tasks. Secondly, across tasks, the mean and variance of mean latency are positively correlated. Compared to a simple task, a complex task has both a larger average mean latency and a larger variance of mean latency, across subjects. Taken together, these associations make the interpretation of the MLD problematic by biasing correlations between the MLD and (a) task mean latencies, (b) the average of the mean latencies, (c) external criteria, and (d) other MLDs. A variety of mean latency transformations were evaluated and, while they differed in their effectiveness, they did not satisfactorily rectify MLD biases. An alternative approach, focusing on scale invariant contrasts of within-subject response latency distributions, is introduced in the conclusion.     

Methodology for the Calculation of Annualized Incremental Risks in Systems of Dams

In the past few years, the field of dam safety has approached risk informed methodologies throughout the world and several methodologies and programs are appearing to aid in the systematization of the calculations. The most common way of implementing these calculations is through the use of event trees, computing event probabilities, and incremental consequences. This methodology is flexible enough for several situations, but its generalization to the case of systems of several dams is complex and its implementation in a completely general calculation methodology presents some problems. Retaining the event tree framework, a new methodology is proposed to calculate incremental risks. The main advantage of this proposed methodology is the ease with which it can be applied to systems of several dams: with a single risk model that describes the complete system and with a single calculation the incremental risks of the system can be obtained, being able to allocate the risk of each dam and of each failure mode. The article shows how both methodologies are equivalent and also applies them to a case study.