Modelling inpatient length of stay by a hierarchical mixture regression via the EM algorithm

The modelling of inpatient length of stay (LOS) has important implications in health care studies. Finite mixture distributions are usually used to model the heterogeneous LOS distribution, due to a certain proportion of patients sustaining-a longer stay. However, the morbidity data are collected from hospitals, observations clustered within the same hospital are often correlated. The generalized linear mixed model approach is adopted to accommodate the inherent correlation via unobservable random effects. An EM algorithm is developed to obtain residual maximum quasi-likelihood estimation. The proposed hierarchical mixture regression approach enables the identification and assessment of factors influencing the long-stay proportion and the LOS for the long-stay patient subgroup. A neonatal LOS data set is used for illustration, (C) 2003 Elsevier Science Ltd. All rights reserved.

Mixture modelling for cluster analysis

Cluster analysis via a finite mixture model approach is considered. With this approach to clustering, the data can be partitioned into a specified number of clusters g by first fitting a mixture model with g components. An outright clustering of the data is then obtained by assigning an observation to the component to which it has the highest estimated posterior probability of belonging; that is, the ith cluster consists of those observations assigned to the ith component (i = 1,..., g). The focus is on the use of mixtures of normal components for the cluster analysis of data that can be regarded as being continuous. But attention is also given to the case of mixed data, where the observations consist of both continuous and discrete variables.

Historical and contemporary mating patterns in remnant populations of the forest tree Fraxinus excelsior L.

Genetic variation at microsatellite markers was used to quantify genetic structure and mating behavior in a severely fragmented population of the wind-pollinated, wind-dispersed temperate tree Fraxinus excelsior in a deforested catchment in Scotland. Remnants maintain high levels of genetic diversity, comparable with those reported for continuous populations in southeastern Europe, and show low interpopulation differentiation (Theta = 0.080), indicating that historical gene exchange has not been limited (Nm = 3.48). We estimated from seeds collected from all trees producing fruits in three of five remnants that F. excelsior is predominantly outcrossing (t(m). = 0.971 +/- 0.028). Use of a neighborhood model approach to describe the relative contribution of local and long-distance pollen dispersal indicates that pollen gene flow into each of the three remnants is extensive (46-95%) and pollen dispersal has two components. The first is very localized and restricted to tens of meters around the mother trees. The second is a long-distance component with dispersal occurring over several kilometers. Effective dispersal distances, accounting for the distance and directionality to mother trees of sampled pollen donors, average 328 m and are greater than values reported for a continuous population. These results suggest that the opening of the landscape facilitates airborne pollen movement and may alleviate the expected detrimental genetic effects of fragmentation.

Application of mixture models to detect differentially expressed genes

An important and common problem in microarray experiments is the detection of genes that are differentially expressed in a given number of classes. As this problem concerns the selection of significant genes from a large pool of candidate genes, it needs to be carried out within the framework of multiple hypothesis testing. In this paper, we focus on the use of mixture models to handle the multiplicity issue. With this approach, a measure of the local FDR (false discovery rate) is provided for each gene. An attractive feature of the mixture model approach is that it provides a framework for the estimation of the prior probability that a gene is not differentially expressed, and this probability can subsequently be used in forming a decision rule. The rule can also be formed to take the false negative rate into account. We apply this approach to a well-known publicly available data set on breast cancer, and discuss our findings with reference to other approaches.

Using mixture models to detect differentially expressed genes

An important and common problem in microarray experiments is the detection of genes that are differentially expressed in a given number of classes. As this problem concerns the selection of significant genes from a large pool of candidate genes, it needs to be carried out within the framework of multiple hypothesis testing. In this paper, we focus on the use of mixture models to handle the multiplicity issue. With this approach, a measure of the local false discovery rate is provided for each gene, and it can be implemented so that the implied global false discovery rate is bounded as with the Benjamini-Hochberg methodology based on tail areas. The latter procedure is too conservative, unless it is modified according to the prior probability that a gene is not differentially expressed. An attractive feature of the mixture model approach is that it provides a framework for the estimation of this probability and its subsequent use in forming a decision rule. The rule can also be formed to take the false negative rate into account.

Professionalism and functional outcomes

A foundation principle of professionalism is listening carefully to clients' needs. This paper reviews current studies that have sought to listen to the needs of people with aphasia and their families. The preliminary evidence to date suggests that people with aphasia have goals that cover the bio-psycho-social spectrum but place a lot of importance on functional outcomes such as participation in life's activities, relationships, and personal self-esteem. In contrast, descriptions of current aphasia management practices reflect a predominantly medical model approach that emphasizes impairment-level goals. This paper suggests that a proportion of speech-language pathologists are not truly listening and responding to their clients' needs. This leads to a mismatch between the therapists' and clients' goals in therapy. The concept of person-centred goal-setting is described. This may contribute to greater alignments of goals and better outcomes of rehabilitation. Learning outcomes: As a result of reading this work, the participant will be able to: (a) have knowledge of criticisms of aphasia therapy by people with aphasia; (b) understand the concept of person-centred goal-setting; (c) understand the complexity of mismatched goals between therapist and client. (c) 2006 Elsevier Inc. All rights reserved.

Mixture models for detecting differentially expressed genes in microarrays

An important and common problem in microarray experiments is the detection of genes that are differentially expressed in a given number of classes. As this problem concerns the selection of significant genes from a large pool of candidate genes, it needs to be carried out within the framework of multiple hypothesis testing. In this paper, we focus on the use of mixture models to handle the multiplicity issue. With this approach, a measure of the local FDR (false discovery rate) is provided for each gene. An attractive feature of the mixture model approach is that it provides a framework for the estimation of the prior probability that a gene is not differentially expressed, and this probability can subsequently be used in forming a decision rule. The rule can also be formed to take the false negative rate into account. We apply this approach to a well-known publicly available data set on breast cancer, and discuss our findings with reference to other approaches.

On a resampling approach for tests on the number of clusters with mixture model-based clustering of tissue samples

We consider the problem of assessing the number of clusters in a limited number of tissue samples containing gene expressions for possibly several thousands of genes. It is proposed to use a normal mixture model-based approach to the clustering of the tissue samples. One advantage of this approach is that the question on the number of clusters in the data can be formulated in terms of a test on the smallest number of components in the mixture model compatible with the data. This test can be carried out on the basis of the likelihood ratio test statistic, using resampling to assess its null distribution. The effectiveness of this approach is demonstrated on simulated data and on some microarray datasets, as considered previously in the bioinformatics literature. (C) 2004 Elsevier Inc. All rights reserved.

The traditional rationale of the arm's length approach to transfer pricing - should the separate accounting model be maintained for modern multinational entities?

This article examines the current transfer pricing regime to consider whether it is a sound model to be applied to modern multinational entities. The arm's length price methodology is examined to enable a discussion of the arguments in favour of such a regime. The article then refutes these arguments concluding that, contrary to the very reason multinational entities exist, applying arm's length rules involves a legal fiction of imagining transactions between unrelated parties. Multinational entities exist to operate in a way that independent entities would not, which the arm's length rules fail to take into account. As such, there is clearly an air of artificiality in applying the arm's length standard. To demonstrate this artificiality with respect to modern multinational entities, multinational banks are used as an example. The article concluded that the separate entity paradigm adopted by the traditional transfer pricing regime is incongruous with the economic theory of modern multinational enterprises.

The Bazhanov-Stroganov model from 3D approach

We apply a three-dimensional approach to describe a new parametrization of the L-operators for the two-dimensional Bazhanov-Stroganov (BS) integrable spin model related to the chiral Potts model. This parametrization is based on the solution of the associated classical discrete integrable system. Using a three-dimensional vertex satisfying a modified tetrahedron equation, we construct an operator which generalizes the BS quantum intertwining matrix S. This operator describes the isospectral deformations of the integrable BS model.

The tiered model of psychosocial intervention in cancer: A community based approach

Clinical practice guidelines for the management of psychosocial distress in people with cancer have been produced ill Australia and North America and these provide direction for the provision of psychosocial care for patients with cancer and their families. This report describes a tiered intervention model to operationalise psychosocial care ill oncology in the community and Outlines a framework for integrating services across sectors. Copyright (c) 2005 John Wiley & Soils, Ltd.