Exact moments of the symmetric cubic assignment statistic

Hubert (1987Assignment Methods in Combinatorial Data Analysis) presented a class of permutation, or random assignment, techniques for assessing correspondence between general k-dimensional proximity measures on a set of “objects.” A major problem in higher-order assignment models is the prohibitive level of computation that is required. We present the first three exact moments of a test statistic for the symmetric cubic assignment model. Efficient computational formulas for the first three moments have been derived, thereby permitting approximation of the permutation distribution using well-known methods.     

Using a mixture model for multiple imputation in the presence of outliers: the 'Healthy for life' project

Summary.  We consider the problem of obtaining population-based inference in the presence of missing data and outliers in the context of estimating the prevalence of obesity and body mass index measures from the 'Healthy for life' study. Identifying multiple outliers in a multivariate setting is problematic because of problems such as masking, in which groups of outliers inflate the covariance matrix in a fashion that prevents their identification when included, and swamping, in which outliers skew covariances in a fashion that makes non-outlying observations appear to be outliers. We develop a latent class model that assumes that each observation belongs to one of K unobserved latent classes, with each latent class having a distinct covariance matrix. We consider the latent class covariance matrix with the largest determinant to form an 'outlier class'. By separating the covariance matrix for the outliers from the covariance matrices for the remainder of the data, we avoid the problems of masking and swamping. As did Ghosh-Dastidar and Schafer, we use a multiple-imputation approach, which allows us simultaneously to conduct inference after removing cases that appear to be outliers and to promulgate uncertainty in the outlier status through the model inference. We extend the work of Ghosh-Dastidar and Schafer by embedding the outlier class in a larger mixture model, consider penalized likelihood and posterior predictive distributions to assess model choice and model fit, and develop the model in a fashion to account for the complex sample design. We also consider the repeated sampling properties of the multiple imputation removal of outliers.     

Estimation for hidden Markov random fields

A finite state Markov random field is noisily observed via a second finite state process. The parameters of the model are estimated, as well as the most likely signal given the observations.     

A framework for progressively improving small area population estimates

Summary.  The paper presents a framework for small area population estimation that enables users to select a method that is fit for the purpose. The adjustments to input data that are needed before use are outlined, with emphasis on developing consistent time series of inputs. We show how geographical harmonization of small areas, which is crucial to comparisons over time, can be achieved. For two study regions, the East of England and Yorkshire and the Humber, the differences in output and consequences of adopting different methods are illustrated. The paper concludes with a discussion of how data, on stream since 1998, might be included in future small area estimates.     

A MODEL FOR COLLABORATIVE TEAM PROCESSING IN BRIEF SYSTEMIC FAMILY THERAPY*

While there has been considerable growth in recent years in the use of collaborative teamwork in Systemic Family Therapy, there has been a dearth of literature concerning the process of team functioning. Based upon a careful analysis of actual teamwork, a model for conducting more efficient and effective team conferences has been developed. The ensuing discussion examines the risks in working in teams and proposes ways to counteract these. Further avenues of research are suggested.     

Do Personality Changes Occur in Parents Receiving Behavioral Family Therapy?

The present outcome study is a preliminary report on whether personality changes occur in parents receiving behavioral family therapy. Behavioral techniques for changing the identified patient's presenting problem were taught to the parents and each family member was given a weekly behavioral homework assignment intended to change the dysfunctional interactions assessed in the family.
An analysis of pre and post measures using Cattell's 16PF questionnaire showed a significant decrease in the parent's self-sufficiency index, indicating increased group dependence. The mean number of sessions was 12.6. The results of this study raise questions about the nature of the personality changes occurring in family therapy of this type. Family therapists, often-times assuming the role of the "expert" for the family, may be unwittingly fostering group dependence and losses in confidence for parents receiving such family guidance.