Kinship care: Two case management models

Children in the care and custody of the state are increasingly placed with kin rather than in unrelated foster homes. Current estimates suggest that 400,000 children are in kinship care arrangements, with a projected increase to over a half million by 1995 (Center for the Study of Social Policy, 1990). This article provides an overview of the trend toward increasing use of kinship care for foster children and the reasons for this development. It then presents the case management models currently used in kinship care cases by two large public child welfare agencies, and it concludes with discussion of these models and their implications.     

A generalized framework for modelling ordinal data

In several applied disciplines, as Economics, Marketing, Business, Sociology, Psychology, Political science, Environmental research and Medicine, it is common to collect data in the form of ordered categorical observations. In this paper, we introduce a class of models based on mixtures of discrete random variables in order to specify a general framework for the statistical analysis of this kind of data. The structure of these models allows the interpretation of the final response as related to feeling, uncertainty and a possible shelter option and the expression of the relationship among these components and subjects’ covariates. Such a model may be effectively estimated by maximum likelihood methods leading to asymptotically efficient inference. We present a simulation experiment and discuss a real case study to check the consistency and the usefulness of the approach. Some final considerations conclude the paper.     

An urn model to construct an efficient test procedure for response adaptive designs

We study the statistical performance of different tests for comparing the mean effect of two treatments. Given a reference classical test \({\mathcal {T}}_0\), we determine which sample size and proportion allocation guarantee to a test \({\mathcal {T}}\), based on response-adaptive design, to be better than \({\mathcal {T}}_0\), in terms of (a) higher power and (b) fewer subjects assigned to the inferior treatment. The adoption of a response-adaptive design to implement the random allocation procedure is necessary to ensure that both (a) and (b) are satisfied. In particular, we propose to use a Modified Randomly Reinforced Urn design and we show how to perform the model parameters selection for the purpose of this paper. Then, the opportunity of relaxing some assumptions on treatment response distributions is presented. Results of simulation studies on the test performance are reported and a real case study is analyzed.     

Modelling spatio-temporal air pollution data from a mobile monitoring station

ABSTRACT

Environmental data is typically indexed in space and time. This work deals with modelling spatio-temporal air quality data, when multiple measurements are available for each space-time point. Typically this situation arises when different measurements referring to several response variables are observed in each space-time point, for example, different pollutants or size resolved data on particular matter. Nonetheless, such a kind of data also arises when using a mobile monitoring station moving along a path for a certain period of time. In this case, each spatio-temporal point has a number of measurements referring to the response variable observed several times over different locations in a close neighbourhood of the space-time point. We deal with this type of data within a hierarchical Bayesian framework, in which observed measurements are modelled in the first stage of the hierarchy, while the unobserved spatio-temporal process is considered in the following stages. The final model is very flexible and includes autoregressive terms in time, different structures for the variance-covariance matrix of the errors, and can manage covariates available at different space-time resolutions. This approach is motivated by the availability of data on urban pollution dynamics: fast measures of gases and size resolved particulate matter have been collected using an Optical Particle Counter located on a cabin of a public conveyance that moves on a monorail on a line transect of a town. Urban microclimate information is also available and included in the model. Simulation studies are conducted to evaluate the performance of the proposed model over existing alternatives that do not model data over the first stage of the hierarchy.     

The mental health status of Latino children in the public child welfare system: a look at the role of generation and origin

As the number of Latino children in public child welfare continues to grow, it is necessary to understand how their mental health is faring. The paper examines emotional and behavioural needs among Latino children who had contact with the public child welfare system. The purpose of this longitudinal study was twofold: to examine the severity of emotional and behavioural problems, and to assess the predictive role of generation status and Latino origin. Latent growth models were completed using the National Survey on Children and Adolescent Well‐Being. The predictive model for the externalizing CBCL scale revealed that generation status and Latino origin were significant predictors. At baseline, Puerto Rican children exhibited higher rates of externalizing problems compared with Mexican children. Over time children who were first/second generation tended to have lower scores compared with the third‐plus generation children. Implications for practise are discussed.     

Improvising Prescription: Evidence from the Emergency Room

Global medical practice is increasingly standardizing through evidence‐based approaches and quality certification procedures. Despite this increasing standardization, medical work in emergency units necessarily involves sensitivity to the individual, the particular and the unexpected. While much medical practice is routine, important improvisational elements remain significant. Standardization and improvisation can be seen as two conflicting logics. However, they are not incompatible, although the occurrence of improvisation in highly structured and institutionally complex environments remains underexplored. The study presents the process of improvisation in the tightly controlled work environment of the emergency room. The authors conducted an in situ ethnographic observation of an emergency unit. An inductive approach shows professionals combining ostensive compliance with protocols with necessary and occasional ‘underlife’ improvisations. The duality of improvisation as simultaneously present and absent is related to pressures in the institutional domain as well as to practical needs emerging from the operational realm. The intense presence of procedures and work processes enables flexible improvised performances that paradoxically end up reinforcing institutional pressures for standardization.     

Ordinal models and generalized estimating equations to evaluate disease severity

Many assays have been carried out in Capsicum spp. in order to evaluate its resistance to Phytophthora capsici , which causes blight and considerable yield loss. An assay aiming at the selection of resistant pepper and bell pepper genotypes to P. capsici was jointly performed in the laboratory of the Phytopathological Clinic of Entomology, Phytopathology and Agricultural Zoology and in the experimental area of the Plant Production Department, both located at ESALQ, University of São Paulo, Brazil. The data set for this assay comes from ordinal categorized random variables, whose analysis does not generally take into account the ordinal nature of the responses, but instead, builds indexes, among other measures, in order to evaluate the resistance of the studied genotypes. This work presents ordinal generalized linear fits in order to evaluate blight severity as well as to identify and select new resources to the pathogen. It also analyses the estimating equations proposed by Liang & Zeger (1986a, b) in order to obtain an infection pattern for the disease. From the fit of the cumulative logit models, valuable genotypes are identified for genetic breeding programs.