The Role of Systematic Reviews and the Campbell Collaboration in the Realization of Evidence-Informed Practice

Evidence-informed practice asks practitioners and policy-makers to integrate current best evidence with client context in order to provide meaningful and potentially effective services across a range of presenting problems. Done correctly, systematic reviews are a crucial part of this process, providing social workers and other helping professionals with transparent, rigorous, and informative syntheses of research in a given area. This paper makes clear the need for systematic reviews in social work, briefly explains what systematic reviews are and how they are made, and describes the role of the Campbell Collaboration in creating a world library of systematic reviews.     

An estimator of relative potency

The Kolmogorov-Sxnirnov statistic is used as a basis for defining nonparaim trie point and interval estimators for the relative potency of a test preparation with respect to a standard preparation These estimators compare favorably with those proposed by Sen (1963) if the dosage distribuiton has heavy mass in either of its tails.     

Ready or not: uses of the stages of change model in child welfare

This article reviews the popular stages of change model, its potential applications in child welfare, and relevant research. Empirical evidence indicates that behavioral change does not occur in a series of stages. The article considers the validity of the stage model, its underlying assumptions, and other conceptualizations of readiness for change. Although the stage model may have some heuristic value, the empirical evidence suggests that its practical applications are severely limited.     

On minimum distance estimation of location based on the kolmogorov statistic

The asymptotic distribution is derived for the minimum distance estimator of a location parameter based on the Kolmogorov goodness of fit statistic. The distribution is expressed in terms of the distribution of a functional of a Brownian bridge. An upper bound is obtained for the length of the confidence interval based on the Kolmogorov statistic. A simulation study with sample sizes 10 and 20 compares the length of the interval based on the Kolmogorov statistic to the length of the interval based on the maximum likelihood estimator. Another simulation shows the effect of model misspecification on the coverage probabilities of the interval based on the Kolmogorov statistic.     

Estimating operational costs in an electric utility

Generation expansion planning in the electric utility industry requires consideration of uncertainties in both the demand and supply of electric power. The expected demand is usually expressed via a load-duration curve, while, on the supply side, each generating unit has a given nameplate capacity and a predicted reliability. This paper focuses on considerations of the supply-side uncertainties and their effects on estimating operating costs in electric utility planning. However, the methods and analysis developed in this paper may be applicable to a wider class of production planning problems which deal with any nonstorable product with time varying demand. Two methods for estimating the energy generation from each generating unit are compared. The first is the method of probabilistic simulation, while the second involves a heuristic technique usually denoted the derating method. A bias inherent in the derating method is examined by comparing it with a probabilistic simulation method. The bias is examined for various load curve shapes. In certain cases, a closed form expression for the bias is obtained. However, a closed form expression of the bias for an arbitrary load curve is difficult to achieve. In these situations some examples are studied in which the trend of the relative bias among plants in the loading order is examined. Finally, the bias is examined using actual 1977 load and supply data for some New England utilities.