Forecasting expenditure on capital projects

S-curves are widely used for planning, forecasting and control of cost, time and resources of a project. In this paper, a comparison of two S-curve models developed at the Department of Health and Social Security (DHSS) and Bradford University is carried out both from the viewpoint of predictive accuracy and ease of use. The models are validated using expenditure data for 21 recent U.K. health building projects. Methods of least squares is used to estimate the parameters of the two models. These parameters are categorized according to the total cost of the projects. Both the models are shown to be of comparable accuracy for fitting actual expenditure data. The DHSS model has a major advantage of simplicity of form and use, although the slightly greater mathematical complexity of the Keller-Singh model is off-set by the readily interpretable nature of its form and basic parameters. It is concluded that both or either of the models could be used by clients/contractors for effective planning and control of project costs.     

EVALUATING FAMILY THERAPY: DIVERGENT METHODS, DIVERGENT FINDINGS

This study reports on a triangulation strategy for assessing family interaction, involving family members, their therapist and coders independently viewing videotapes. Utilizing a standardized scale, the Beavers-Timberlawn Model of Family Competence, the study found weak agreement between paired assessments within the family triad, and within the therapist-coder dyad. In addition, more complex scaling techniques such as composite "family scores" or discrepancy scores between family member dyads added no predictive power. The findings suggest that a "limit of concordance" may exist when comparing varying raters' assessments of a given family, and that methodological and/or scaling strategies designed to maximize agreement may be both fruitless and diversionary.     

Mixture models in measurement error problems, with reference to epidemiological studies

Summary. The paper focuses on a Bayesian treatment of measurement error problems and on the question of the specification of the prior distribution of the unknown covariates. It presents a flexible semiparametric model for this distribution based on a mixture of normal distributions with an unknown number of components. Implementation of this prior model as part of a full Bayesian analysis of measurement error problems is described in classical set-ups that are encountered in epidemiological studies: logistic regression between unknown covariates and outcome, with a normal or log-normal error model and a validation group. The feasibility of this combined model is tested and its performance is demonstrated in a simulation study that includes an assessment of the influence of misspecification of the prior distribution of the unknown covariates and a comparison with the semiparametric maximum likelihood method of Roeder, Carroll and Lindsay. Finally, the methodology is illustrated on a data set on coronary heart disease and cholesterol levels in blood.     

Latent variable techniques for categorical data

Two useful statistical methods for generating a latent variable are described and extended to incorporate polytomous data and additional covariates. Item response analysis is not well-known outside its area of application, mainly because the procedures to fit the models are computer intensive and not routinely available within general statistical software packages. The linear score technique is less computer intensive, straightforward to implement and has been proposed as a good approximation to item response analysis. Both methods have been implemented in the standard statistical software package GLIM 4.0, and are compared to determine their effectiveness.     

The simulation of industrial robot systems

This paper describes the GRASP computer aided design system for modelling and evaluating industrial robot workplaces. GRASP satisfies a range of simulation needs within the context of designing, implementing and operating industrial robotic systems. The GRASP software may be used to investigate robots operating by themselves or, more likely, as part of an integrated cell. Facilities within GRASP assist workplace layout, position and velocity evaluations, clash detection and co-ordination between items. A robot library exists and is being extended, and an embryo off-line programming facility has been used under restricted conditions. GRASP has been used to help solve a wide range of practical industrial robot problems and has proved itself technically, and also as an educational tool, by showing how a proposed system would operate. The paper describes the facilities within GRASP.     

Evaluating the effectiveness of a school drug and alcohol prevention curriculum: a new look at "Here's Looking at You, Two"

The article reports on the results of an evaluation of a school drug and alcohol prevention curriculum marketed under the title, "Here's Looking at You, Two." Previous evaluations, unreported in the literature and having unresolved methodological problems, have found that while the program appears effective at transmitting information regarding drug and alcohol abuse, it has not been effective at changing the underlying attitudes and behaviors that, in part, explain substance abuse. Employing a more rigorous methodology, our examination of a relatively large sample across five school districts provides support for previous findings. Over the short-term of one year, the program was particularly effective at transmitting substance information to primary and middle school students. The program, however, produced very little of the expected effect on the underlying attitudes that are critical to changing substance abuse behaviors.