Comparative probability for conditional events: A new look through coherence

We study, from the standpoint of coherence, comparative probabilities on an arbitrary familyE of conditional events. Given a binary relation ·, coherence conditions on · are related to de Finetti's coherent betting system: we consider their connections to the usual properties of comparative probability and to the possibility of numerical representations of ·. In this context, the numerical reference frame is that of de Finetti's coherent subjective conditional probability, which is not introduced (as in Kolmogoroff's approach) through a ratio between probability measures.Another relevant feature of our approach is that the family & need not have any particular algebraic structure, so that the ordering can be initially given for a few conditional events of interest and then possibly extended by a step-by-step procedure, preserving coherence.     

Social forecasting: An integral part of corporate planning?

The increasing need for business to monitor the social dimensions of its environment and, hopefully make some forecasts of future trends has met with some constructive response from academics and consultants although not as yet on a very liberal scale. The published literature does not indicate to what extent companies in general attemp social forecasting and, where they do, the degree of integration which exists within their corporate planning systems. The authors, therefore, decided to survey a sample of British organizations to see if they could shed some light on these issues and thereby add some information to the excellent accounts of individual cases of social forecasting in, they suspect, the more advanced and atypical companies. The survey suggests a general picture of: awareness of the value of social forecasting; fairly widespread ignorance of the techniques which do exist, primitive though these may largely be; successful integration of social forecasting into the corporate planning systems of a substantial number of organizations but not in the majority.     

Assessment of Composite Indicators Using the ANOVA Model Combined with Multivariate Methods

The synthesis of a number of single observed indicators into a unique composite indicator involves various subjective choices related, for instance, to the type of combination (linear, non-linear) and to the aggregation method (simple average, geometric average) used in its construction. Thus, it is clearly important to analyse the variability of a composite indicator according to all possible alternatives before employing it in any decision-making process. Within such a framework, in this paper, we present a new approach based on a combination of explorative and confirmative analyses aiming to investigate the impact of different subjective choices on the variability of composite indicators. This new approach also allows the analysis of the related individual differences among the statistical units and the use of external information on the same units to enhance the interpretation of the final results.     

Caregivers' perspectives on the SafeCare® programme: Implementing an evidence‐based intervention for child neglect

This qualitative study examined caregivers' experiences with SafeCare®, an evidence‐based programme that focuses on child neglect through modules on health, safety, and parenting. Shortly after completing SafeCare, 30 caregivers participated in a semi‐structured interview about their experiences with the programme. Overall, caregivers indicated that the programme helped with improvements in their parenting skills. Among the factors that contributed to a positive experience were the simplicity of language, the skills‐based approach, and the quality of the relationship with the SafeCare provider. Caregivers also noted several factors that made it difficult to fully benefit from the programme, including financial constraints, removal of their child from the home, and general distrust towards the child welfare system. Findings provide relevant information for SafeCare providers in terms of identifying areas that work well for caregivers completing the programme, as well as areas that might serve as impediments. Implications for contemporary child welfare practice are also considered.     

Studying the dependence between ordinal-nominal categorical variables via orthogonal polynomials

In situations where the structure of one of the variables of a contingency table is ordered recent theory involving the augmentation of singular vectors and orthogonal polynomials has shown to be applicable for performing symmetric and non-symmetric correspondence analysis. Such an approach has the advantage of allowing the user to identify the source of variation between the categories in terms of components that reflect linear, quadratic and higher-order trends. The purpose of this paper is to focus on the study of two asymmetrically related variables cross-classified to form a two-way contingency table where only one of the variables has an ordinal structure.     

Prevention training of paraprofessionals in the schools: an examination of relevancy and effectiveness

Prevention training programs for paraprofessional school personnel are examined in this article. Prevention training for the reduction of student alcohol and other drug use, incorporating a student well-being model, is described and evaluated. The prevention training, entitled "Enhancing Student Well-Being," took place in two urban school districts with over 200 paraprofessional school personnel participating. The training was evaluated using measures of knowledge gained, self-efficacy, and participant satisfaction. Pre- and post-training differences showed consistent gains in participant efficacy expectations but less consistent gains in outcome expectations and knowledge. Participant satisfaction and self-reports of knowledge enhanced and skill improvement were uniformly high across all training programs. Implications for inservice prevention training of paraprofessionals are discussed.     

Small area estimation for longitudinal surveys

Over the last few years many studies have been carried out in Italy to identify reliable small area labour force indicators. Considering the rotated sample design of the Italian Labour Force Survey, the aim of this work is to derive a small area estimator which borrows strength from individual temporal correlation, as well as from related areas. Two small area estimators are derived as extensions of an estimation strategies proposed by Fuller (1990) for partial overlap samples. A simulation study is carried out to evaluate the gain in efficiency provided by our solutions. Results obtained for different levels of autocorrelation between repeated measurements on the same outcome and different population settings show that these estimators are always more reliable than the traditional composite one, and in some circumstances they are extremely advantageous.The present paper is financially supported by Murst-Cofin (2001) Lutilizzo di informazioni di tipo amministrativo nella stima per piccole aree e per sottoinsiemi della popolazione (National Coordinator Prof. Carlo Filippucci).     

Nonconglomerative coherent conditional probabilities in statistical inference

Noteworthy connections among conglomerability, countable additivity and coherence are discussed in detail, reaching the conclusion that nonconglomerable conditional probabilities must not be doomed and play a significant role in statistical inference. Extended and updated version of a contributed paper presented at the International Conference on “Information Processing and Management of Uncertainty in knowledge-based systems”, IPMU 2004, Perugia, Italy.