Data quality in evaluation of an alcohol-related harm prevention program

The authors report the reliability and convergent validity in a sample of college students for 27 composite scales and two items covering alcohol use, cigarette smoking, marijuana use, and other drug use; beliefs relating to alcohol use; perceived norms for alcohol-related behavior; harm prevention skills; intentions to take prevention action; harm prevention action taken; risk taken; experienced harm; and other health-related behaviors and person characteristics. Data quality assessment strategies and missing data procedures were illustrated for large, multivariate, longitudinal data sets. Results indicate 23 of the 27 composite scales had at least acceptable reliability, and the remaining 4 composite scales had at least marginally acceptable reliability. At least moderate construct validity was demonstrated for 25 scales.     

College students and tattoos. Influence of image,identity, family,and friends

Tattoos are popular among many groups of people. College students from a large university in the southwestern United States were queried using the 134-item Armstrong Team Tattoo Attitude Survey. Findings documents a progressive increase in tattooing and reflect significant support for tattoos, even from non-tattooed students. Similar and positive demographic characteristics were present in individuals who were both non-tattooed and tattooed. In addition, tattooed people were viewed positively, even among non-tattooed respondents. Friends significantly affected procurement and possession of tattoos, whereas of all family members, the sister was the only significant influence. Overall, friends, identity, and image seem to be the major influences for obtaining tattoos.     

Success and Failure of MRP II Implementation

This paper assesses the reasons for the success or failure of manufacturing resource planning (MRPII) implementation projects. It begins by discussing the literature and research on success and failure of these systems and presents evidence from cases prepared by the authors. The paper is not concerned to prescribe ‘best practice’ for MRP implementation. The first section reviews the relevant literature and concludes that there is a divergence of opinion as to what constitutes success, raising questions on the usefulness of current methods of establishing whether implementation is successful. The latter section of the paper uses results from longitudinal (process) research carried out by the authors. This starts with a discussion of what counts for success. The discussion highlights the importance of understanding the full potential of MRPII in effecting change of organizational structures, cultures and practice. Several factors that contribute towards MRPII failure are next considered. Finally,‘big bang’style implementations, such as those recommended by the Ollie Wight organization, are most likely to be successful if the organization follows a strategic approach to planning. There also needs to be a high degree of fit between organizational structure, culture and the demands of the MRPII system.     

Improving child welfare performance through supervisory use of client outcome data

Despite their benefits, there is little evidence that outcome data are being widely used by program managers or field level supervisors. Three interdependent factors that facilitate the use of outcome data are well-constructed reports, and organizational culture that supports learning and outcome achievement, and managerial skills in interpreting data and taking relevant action. This article describes an outcome reporting package and training oriented toward frontline supervisors to help them use outcome data, shape a learning culture, interpret data, and take focused action toward improving outcomes for children and families.     

Barroom aggression in Hoboken, New Jersey: don't blame the bouncers!

Relying on a structured observation guide listing a large number of variables shown to be good predictors of aggression in bars by past researchers, trained observers spent a total of 444 hours collecting data in 25 licensed drinking establishments in Hoboken, New Jersey. Observations took place at two separate time periods, 7:30pm-10:30pm and 11:00pm-2:00am, on Thursday, Friday, and Saturday nights. Logistic regression analyses revealed the absence of bouncers and doormen as the strongest predictor of aggression in Hoboken barrooms. This is a particularly important finding considering the frequency with which bouncers and doormen are vilified in the available research on barroom aggression. Several practical prevention strategies aimed at reducing aggression in bars are proposed.     

The racial geography of child welfare: toward a new research paradigm

This article examines the community-level impact of concentrated child welfare agency involvement in African American neighborhoods. Based on interviews of 25 African American women in a Chicago neighborhood, the study found that residents were aware of intense agency involvement in their neighborhood and identified profound effects on social relationships including interference with parental authority, damage to children's ability to form social relationships, and distrust among neighbors. The study also discovered a tension between respondents' identification of adverse consequences of concentrated state supervision for family and community relationships and neighborhood reliance on agency involvement for needed financial support. The author discusses the implications of these findings for a new research paradigm aimed at understanding the community-level effects of racial disproportionality.     

On convergence of the EM algorithmand the Gibbs sampler

In this article we investigate the relationship between the EM algorithm and the Gibbs sampler. We show that the approximate rate of convergence of the Gibbs sampler by Gaussian approximation is equal to that of the corresponding EM-type algorithm. This helps in implementing either of the algorithms as improvement strategies for one algorithm can be directly transported to the other. In particular, by running the EM algorithm we know approximately how many iterations are needed for convergence of the Gibbs sampler. We also obtain a result that under certain conditions, the EM algorithm used for finding the maximum likelihood estimates can be slower to converge than the corresponding Gibbs sampler for Bayesian inference. We illustrate our results in a number of realistic examples all based on the generalized linear mixed models.     

Likelihood‐based inference for correlated diffusions

The authors address the problem of likelihood‐based inference for correlated diffusions. Such a task presents two issues; the positive definite constraints of the diffusion matrix and the likelihood intractability. The first issue is handled by using the Cholesky factorization on the diffusion matrix. To deal with the likelihood unavailability, a generalization of the data augmentation framework of Roberts and Stramer [Roberts and Stramer (2001) Biometrika 88(3), 603–621] to d‐dimensional correlated diffusions, including multivariate stochastic volatility models, is given. The methodology is illustrated through simulated and real data sets. The Canadian Journal of Statistics 39: 52–72; 2011 © 2011 Statistical Society of Canada