Testing for lack of fit in linear multiresponse models based on exact or near replicates

Three procedures for testing the adequacy of a proposed linear multiresponse regression model against unspecified general alternatives are considered. The model has an error structure with a matrix normal distribution which allows the vector of responses for a particular run to have an unknown covariance matrix while the responses for different runs are uncorrelated. Furthermore, each response variable may be modeled by a separate design matrix. Multivariate statistics corresponding to the classical univariate lack of fit and pure error sums of squares are defined and used to determine the multivariate lack of fit tests. A simulation study was performed to compare the power functions of the test procedures in the case of replication. Generalizations of the tests for the case in which there are no independent replicates on all responses are also presented.     

THE PROCESS OF CHANGE IN COUPLES THERAPY: A QUALITATIVE INVESTIGATION

Open-ended interviews with 24 couples therapy clients regarding their experience of the process of change revealed shifts in clusters of affect, communication, and cognition. Six additional contextual preconditions for change were also identified. The change process within couples was uniformly reported to be gradual.     

Tightened single-level continuous sampling plan

In this paper, a new tightening concept has been incorporated into the single-level continuous sampling plan CSP-1, such that quality degradation will warrant sampling inspection to cease beyond a certain number of sampled items, until new evidence of good quality is established. The expressions of the performance measures for this new plan, such as the operating characteristic, average outgoing quality and average fraction inspected, are derived using a Markov chain model. The advantage of the tightened CSP-1 plan is that it is possible to lower the average outgoing quality limit.     

A Note on Regression-Type Estimators Using Multiple Auxiliary Information

Kiregyera (1984), Mukerjee, Rao & Vijayan (1987), and Tripathi & Ahmed (1995) considered a number of regression-type estimators where information on two auxiliary variables related to study variable is available at different levels. Mukerjee et al . (1987) suggested three estimators and computed their mean square errors, but the computations seem to be incorrect. This note corrects them, and finds their estimators are no better than that of Kiregyera (1984). The estimator suggested by Tripathi & Ahmed (1995) is the best in the sense of having the smallest mean square error.     

Social Policy at the 2004 Election

Social policy appeared to be a key battleground at the 2004 Australian Federal election. Opposition Leader Latham announced major policies on Medicare, family support and taxation, and schools funding during the election campaign. Using sample survey data from the Australian Election Study 2004, this paper analyses how these policies may have influenced voters. In brief, although a significant proportion of electors identified these issues as being extremely important to them when they were deciding about how to vote, many made up their mind about how to vote around the time of the announcement of the election or before. This mitigated the potential effect that these major policies could have on the election outcome. Nevertheless, these policies were important and Labor had a significant policy advantage amongst those who were late deciders about how to cast their vote.     

Intra‐Household Specialization in Housework in the United States and Denmark*

Objective. Focusing on housework activities, we hypothesize that the degree of specialization is influenced by economic notions of efficiency, as well as by time constraints and egalitarian values. Methods. Employing time‐use data on U.S. and Danish couples, we construct a composite index measure of intra‐household specialization. We analyze the comparability of reported time use and our specialization index using different types of data, and then model specialization using a multivariate two‐limit Tobit. Results. We find evidence that Danish households specialize less than U.S. households and that children, particularly preschool‐aged children, are associated with significantly increased specialization in the United States but not in Denmark. Conclusions. We postulate that the more egalitarian social structure in Scandinavia is a driving force behind the lower rate of specialization observed in Denmark. Further, we believe the subsidized child‐care services provided by the Danish welfare system reduce the impact children have on specialization in ordinary housework tasks.     

Survival dilemmas: Case study of an adult child of a schizophrenic parent

This article describes aspects of the treatment of an adult child of a schizophrenic parent. Many theories on irrationality in the family setting illuminate the range of impingement on the child's reality when a parent is disturbed in this way. Current research has absorbed itself in interpretations of data on risk, vulnerability, disorder, and early trauma, which have implications for prevention as well as therapeutic treatment of the adult survivor. Profound effects on Ms. P's early development are elaborated in the therapy, in which the treatment stance is influenced by Kohut's theories of the self, particularly as applied to the establishment within the holding environment of specific transferences that facilitate reconstructive work.     

Model-based clustering for social networks

Summary.  Network models are widely used to represent relations between interacting units or actors. Network data often exhibit transitivity, meaning that two actors that have ties to a third actor are more likely to be tied than actors that do not, homophily by attributes of the actors or dyads, and clustering. Interest often focuses on finding clusters of actors or ties, and the number of groups in the data is typically unknown. We propose a new model, the latent position cluster model , under which the probability of a tie between two actors depends on the distance between them in an unobserved Euclidean 'social space', and the actors' locations in the latent social space arise from a mixture of distributions, each corresponding to a cluster. We propose two estimation methods: a two-stage maximum likelihood method and a fully Bayesian method that uses Markov chain Monte Carlo sampling. The former is quicker and simpler, but the latter performs better. We also propose a Bayesian way of determining the number of clusters that are present by using approximate conditional Bayes factors. Our model represents transitivity, homophily by attributes and clustering simultaneously and does not require the number of clusters to be known. The model makes it easy to simulate realistic networks with clustering, which are potentially useful as inputs to models of more complex systems of which the network is part, such as epidemic models of infectious disease. We apply the model to two networks of social relations. A free software package in the R statistical language, latentnet, is available to analyse data by using the model.