Lessons Learned From the First-Year Evaluation of a Small-Scale Home Visitation Program

ABSTRACT

Home visitation programs to prevent child maltreatment are offered in many communities. Agencies in these communities want to help families in need while under increased pressure to provide effective services. Funding is limited and competitive; some agencies might choose to limit funds spent on supervision, training, and evaluation as a way to provide more direct service. In this article, we use an implementation science framework and the results of an evaluation of a small home visitation program to underscore the importance of ongoing training and supervision, attention to fidelity, and program evaluation. The evaluation included 17 families entering the program during 21 months. Evaluators visited families in their homes at the beginning of the program and again 10 months later. Like many other well-intended, small-scale programs, this one “borrowed” from evidence-based models and expanded enrollment criteria in an attempt to better serve families. Findings from the evaluation suggest that the program, as it was carried out, was not effective at reducing parenting behaviors known to be associated with child maltreatment. We offer advice to funding and community agencies based on these findings and implementation science. Future evaluation research must pay greater attention to fidelity and implementation.     

Influence diagnostics on the coefficient of variation of elliptically contoured distributions

In this article, we study the behavior of the coefficient of variation (CV) of a random variable that follows a symmetric distribution in the real line. Specifically, we estimate this coefficient using the maximum-likelihood (ML) method. In addition, we provide asymptotic inference for this parameter, which allows us to contrast hypothesis and construct confidence intervals. Furthermore, we produce influence diagnostics to evaluate the sensitivity of the ML estimate of this coefficient when atypical data are present. Moreover, we illustrate the obtained results by using financial real data. Finally, we carry out a simulation study to detect the potential influence of atypical observations on the ML estimator of the CV of a symmetric distribution. The illustration and simulation demonstrate the robustness of the ML estimation of this coefficient.     

System of Systems Engineering and Risk Management of Extreme Events: Concepts and Case Study

The domain of risk analysis is expanded to consider strategic interactions among multiple participants in the management of extreme risk in a system of systems. These risks are fraught with complexity, ambiguity, and uncertainty, which pose challenges in how participants perceive, understand, and manage risk of extreme events. In the case of extreme events affecting a system of systems, cause‐and‐effect relationships among initiating events and losses may be difficult to ascertain due to interactions of multiple systems and participants (complexity). Moreover, selection of threats, hazards, and consequences on which to focus may be unclear or contentious to participants within multiple interacting systems (ambiguity). Finally, all types of risk, by definition, involve potential losses due to uncertain events (uncertainty). Therefore, risk analysis of extreme events affecting a system of systems should address complex, ambiguous, and uncertain aspects of extreme risk. To accomplish this, a system of systems engineering methodology for risk analysis is proposed as a general approach to address extreme risk in a system of systems. Our contribution is an integrative and adaptive systems methodology to analyze risk such that strategic interactions among multiple participants are considered. A practical application of the system of systems engineering methodology is demonstrated in part by a case study of a maritime infrastructure system of systems interface, namely, the Straits of Malacca and Singapore.     

Dominance intensity measure within fuzzy weight oriented MAUT: An application

We introduce a dominance intensity measuring method to derive a ranking of alternatives to deal with incomplete information in multi-criteria decision-making problems on the basis of multi-attribute utility theory (MAUT) and fuzzy sets theory. We consider the situation where there is imprecision concerning decision-makers' preferences, and imprecise weights are represented by trapezoidal fuzzy weights. The proposed method is based on the dominance values between pairs of alternatives. These values can be computed by linear programming, as an additive multi-attribute utility model is used to rate the alternatives. Dominance values are then transformed into dominance intensity measures, used to rank the alternatives under consideration. Distances between fuzzy numbers based on the generalization of the left and right fuzzy numbers are utilized to account for fuzzy weights.     

“Living with electronic data interchange: Implementation and practical applications for EDI from the perspective of the ILS vendor,the librarian,and the book vendor,” a report from the ALCTS,automated acquisitions/in-process control systems discussion group session at the ALA midwinter conference,January 1996

Abstract

The libraries in the Western North Carolina Library Network (WNCLN) seek effective ways to provide patrons with a complete list of electronic journals provided through their various aggregator services, so patrons can determine e-journal access to article citations. The WNCLN libraries (Appalachian State University, the University of North Carolina at Asheville, and Western Carolina University) accomplished this through their shared catalog (Innovative Interfaces, Inc. [INNOPAC]), data provided by Serials Solutions, and local computer programming. Brief MARC records, with locally created key titles, provide an interim solution to the complexities of aggregator services. Serials Review 2002; 28:108–112.     

Do Benefits of U.S. Food Assistance Programs for Children Spillover to Older Children in the Same Household?

The Women, Infants and Children (WIC) program targets low-income individuals in nutritionally vulnerable groups in the U.S. The food benefits individuals receive could be shared with other family members or may free a portion of the family budget. National Health and Nutrition Examination Survey data are used to examine whether children who are age-ineligible for WIC (age 5–17), that live in WIC-participating families have healthier diets than similar children in nonparticipating families. Results show children in WIC-participating families score higher on the Healthy Eating Index than children in non participating families. This association is stronger for children in families with two or more WIC participants compared with children living with only one or no WIC participants.     

A class of copulas with piecewise linear horizontal sections

We introduce the class of bivariate copulas with piecewise linear horizontal sections whose graph is composed, at most, of two segments. It is a wide class of copulas which contains some known copulas. We study several properties of the copulas in the new class concerning absolute continuity, singular components, measures of association, concordance ordering, dependence concepts and symmetry. Finally, we provide several examples.     

Multiple Criteria Hierarchy Process with ELECTRE and PROMETHEE

Robust Ordinal Regression (ROR) supports Multiple Criteria Decision Process by considering all sets of parameters of an assumed preference model, that are compatible with preference information elicited by a Decision Maker (DM). As a result of ROR, one gets necessary and possible preference relations in the set of alternatives, which hold for all compatible sets of parameters, or for at least one compatible set of parameters, respectively. In this paper, we propose an extension of ELECTRE and PROMETHEE methods to the case of the hierarchy of criteria, which was never considered before. Then, we adapt ROR to the hierarchical versions of ELECTRE and PROMETHEE methods.