Are Rural Schools Inferior to Urban Schools? A Multilevel Analysis of School Accountability Trends in Kentucky*

Abstract Recent research does not provide clear evidence that rural schools are inferior to urban schools. For example, one prominent study finds that students in rural schools perform less well than their urban counterparts, but other studies using the same national data set have reached divergent conclusions. The present study reassesses the issue using a time series approach to school performance. We investigate the effects of location on school‐level performance and improvement indicators between 1999 and 2003 using a sample of 1,111 Kentucky public schools nested in 170 school districts. Repeated‐observations HLM analysis reveals that rural schools achieve mean annual gains in performance that equal or better their urban counterparts. Furthermore, schools in some nonmetro locations perform on par with metro schools in between‐school baseline score comparisons. A simple answer to the question “Are rural schools inferior?” is not feasible, however, since standards for assessing school quality are changing as a consequence of education reform initiatives at the state and national levels.     

Variational Bayes for estimating the parameters of a hidden Potts model

Hidden Markov random field models provide an appealing representation of images and other spatial problems. The drawback is that inference is not straightforward for these models as the normalisation constant for the likelihood is generally intractable except for very small observation sets. Variational methods are an emerging tool for Bayesian inference and they have already been successfully applied in other contexts. Focusing on the particular case of a hidden Potts model with Gaussian noise, we show how variational Bayesian methods can be applied to hidden Markov random field inference. To tackle the obstacle of the intractable normalising constant for the likelihood, we explore alternative estimation approaches for incorporation into the variational Bayes algorithm. We consider a pseudo-likelihood approach as well as the more recent reduced dependence approximation of the normalisation constant. To illustrate the effectiveness of these approaches we present empirical results from the analysis of simulated datasets. We also analyse a real dataset and compare results with those of previous analyses as well as those obtained from the recently developed auxiliary variable MCMC method and the recursive MCMC method. Our results show that the variational Bayesian analyses can be carried out much faster than the MCMC analyses and produce good estimates of model parameters. We also found that the reduced dependence approximation of the normalisation constant outperformed the pseudo-likelihood approximation in our analysis of real and synthetic datasets.     

Neuropsychiatric complications of traumatic brain injury

Traumatic brain injury (TBI) may be defined as any extracranial mechanical force to the brain that results in any period of loss of consciousness, any loss of memory for events immediately before or after the event, or any alteration in mental status at the time of the event. The major causes are automobile accidents, falls, sporting injuries, and assaults. Many soldiers returning from combat in Afghanistan and Iraq have also experienced TBI. This article provides an overview of the neuropsychiatric complications of TBI, including impairment of consciousness, posttraumatic amnesia, cognitive disorders and dementia, posttraumatic epilepsy, aphasia, depression, mania, psychosis, anxiety disorders, personality changes, aggression, behavioral dyscontrol, fatigue/apathy, and increased risk of suicide. Discussion will focus primarily on issues affecting mental health clinicians. Because mental health providers are more involved in care of chronic issues related to TBI, these issues will be discussed in more detail, although acute neuropsychiatric complications of TBI will be briefly explained.     

Efficient calculation of the normalizing constant of the autologistic and related models on the cylinder and lattice

Summary. Motivated by the autologistic model for the analysis of spatial binary data on the two-dimensional lattice, we develop efficient computational methods for calculating the normalizing constant for models for discrete data defined on the cylinder and lattice. Because the normalizing constant is generally unknown analytically, statisticians have developed various ad hoc methods to overcome this difficulty. Our aim is to provide computationally and statistically efficient methods for calculating the normalizing constant so that efficient likelihood-based statistical methods are then available for inference. We extend the so-called transition method to find a feasible computational method of obtaining the normalizing constant for the cylinder boundary condition. To extend the result to the free-boundary condition on the lattice we use an efficient path sampling Markov chain Monte Carlo scheme. The methods are generally applicable to association patterns other than spatial, such as clustered binary data, and to variables taking three or more values described by, for example, Potts models.     

What does children's art work tell us about gender?

If art is an authentic expression of the self, a sociologist should be able to examine children's art work to see what effect various social agents have had on gender socialization. Inferences could be made from the art work about the socialization process. In this study, the authors examined children's art work to investigate the implicit sex role perceptions of children. The population included 110 students between the ages of nine and 12 in three elementary schools in Texas. 126 pieces of art were examined and 500 independent ratings were made. Results of the study indicated that the content and form of children's art work differ significantly by sex. A gender role perspective was used to explain the pattern.     

In their Own Right: Translating the Policy of Carer Assessment into Practice

Successive legislation has underscored the importance of assessmentsthat are sensitive to the needs of carers and take into accounttheir ability and willingness to continue caring. This papersynthesizes qualitative and quantitative findings from a continuingprogramme of carer-related research that began in 1993 and hascontinued in parallel with legislative changes. It considersthe process and characteristics of carer assessment from theperspectives of carers for individuals with a range of healthand social care needs, and practitioners. This paper exploresthe assessment of carer need over time and highlights the considerableand enduring gap between policy and practice. It considers practitioners’reluctance to offer separate carer assessments, identifies confusionrelating to the interpretation of eligibility criteria and documentsthe limited contribution of health service staff. The need foran evidence-based framework for good practice, that distinguishesbetween carer needs, service provision and carer outcomes, ishighlighted. The paper concludes by identifying key changesthat are necessary to promote future good practice, such asstaff training and information strategies and the need for practitionersto engage with carers as partners in the care process.     

Emotional responses of men and women when labeled nonintelligent and unattractive by various reference groups

The study explored the emotional responses of men and women when labeled nonintelligent and unattractive by various reference groups—child(ren), spouse, father, mother and generalized others. Questionnaires were administered to 151 men and women. The findings indicated that (1) women were more likely than men to experience the label of being unattractive, (2) the label was differentially applied by various reference groups, and (3) women responded to being labeled unattractive with hurt, embarrassment and sadness.