Trends in Adolescent Development Impacting Practice: How Can We Catch Up?

Changes in the mechanisms of communication and advances in brain imaging technology shape understanding and interpretation of the manner in which adolescents process and respond to information and relate to others. Knowledge about how trends in adolescent development should inform practice with adolescents is limited, and yet emerging trends and new discoveries have implications for adolescent relationships, behavior, and well-being. Our purpose was to critically examine the influence of major technological innovations on adolescent development and the impacts on research and practice with vulnerable adolescent populations. We discuss strategies for researchers and practitioners.     

Subjective evaluation of well-being: Problems and prospects

This paper discusses some of the substantive and methodological pitfalls that arise in the subjective evaluation of well-being. The discussion includes illustrative references to the empirical findings of the 1977 Edmonton Area Study. Issues discussed include (1) specific, domain, and global measures; (2) objective states and subjective perceptions; (3) micro and macro units of analysis; and (4) the problem of cultural relativism. It is concluded that it is not yet possible to delineate a simple set of social indicators for use by policy-makers and social planners. Accurate assessment of social well-being currently requires the study of demographic and objective states together with cognitive and evaluational responses and also requires assessment not only at the global ‘general satisfaction’ level but also at more specific levels of analysis.     

A pseudo-complete sample technique for estimation from censored samples

An iterative procedure is presented whereby singly right censored samples are transformed into pseudo-complete samples. This involves the use of order statistics to calculate expected “complete” values of the censored observations. Estimates of the distribution parameters are then calculated by employing standard complete sample estimators. This procedure is applicable to various types of distributions.     

Distribution of Increases in Residual Log Likelihood for Nested Spatial Models

Here we review nested relationships between models in the Matérn family of spatial models. The problem of comparing nested statistical models is straightforward in regular parametric problems via the likelihood ratio statistics and its asymptotic distribution. Here we examine the distribution of increments in residual log likelihood between nested spatial models when the null hypothesis is that the spatial structure is a convex combination of white noise and the de Wijs process, also known by its logarithmic covariance function. This study is carried out by simulation of spatial processes and the important aspects of this work include how to simulate a spatial process of order 0, the lack of strong bias in the estimates of variance components, and the validity of the usual asymptotic results for nested spatial models examined here.     

A Probabilistic Arsenic Exposure Assessment for Children Who Contact Chromated Copper Arsenate (CCA)-Treated Playsets and Decks, Part 2: Sensitivity and Uncertainty Analyses

A probabilistic model (SHEDS-Wood) was developed to examine children's exposure and dose to chromated copper arsenate (CCA)-treated wood, as described in Part 1 of this two-part article. This Part 2 article discusses sensitivity and uncertainty analyses conducted to assess the key model inputs and areas of needed research for children's exposure to CCA-treated playsets and decks. The following types of analyses were conducted: (1) sensitivity analyses using a percentile scaling approach and multiple stepwise regression; and (2) uncertainty analyses using the bootstrap and two-stage Monte Carlo techniques. The five most important variables, based on both sensitivity and uncertainty analyses, were: wood surface residue-to-skin transfer efficiency; wood surface residue levels; fraction of hand surface area mouthed per mouthing event; average fraction of nonresidential outdoor time a child plays on/around CCA-treated public playsets; and frequency of hand washing. In general, there was a factor of 8 for the 5th and 95th percentiles and a factor of 4 for the 50th percentile in the uncertainty of predicted population dose estimates due to parameter uncertainty. Data were available for most of the key model inputs identified with sensitivity and uncertainty analyses; however, there were few or no data for some key inputs. To evaluate and improve the accuracy of model results, future measurement studies should obtain longitudinal time-activity diary information on children, spatial and temporal measurements of residue and soil concentrations on or near CCA-treated playsets and decks, and key exposure factors. Future studies should also address other sources of uncertainty in addition to parameter uncertainty, such as scenario and model uncertainty.     

AN EMPIRICAL EVALUATION OF CONSTANT AND ADAPTIVE COMPUTER FORECASTING MODELS FOR INVENTORY CONTROL

This study compares the performance of one constant model with two adaptive models. MAD and bias were used as criteria for evaluating performance. The results of testing the adaptive models with the constant model were contrary to the expected better performance of the adaptive models; no significant differences were found between the models over known horizontal, trend, and seasonal demand patterns. However, some of the practical advantages of adaptive forecasting models in business suggest their continued use.