Heteroscedastic factor analysis

Factor analysis is a widely used statistical method for exploring and modeling multivariate data. The standard factor analysis model assumes that the underlying factors and errors are independent. This dissertation discusses statistical issues involved in using a new model where factors and errors are uncorrelated but dependent. The proposed model is useful in representing the heteroscedasticity, i.e., the dependency of error variability on individual factor scores. Statistical analysis based on the model is not straightforward, because factors are not directly observable;Graphical diagnostic procedures for detecting the factor-error dependency or the heteroscedastic error structure are suggested. The effect of the heteroscedasticity on the standard factor analysis inference procedures is investigated. It is shown that the inferences for the factor loading parameters are still approximately valid under modest factor-error dependency. Two procedures for fitting the heteroscedastic factor analysis model are proposed. Both methods are developed without assuming particular distributional forms for factors and errors. Asymptotic inference procedures for the model parameters and for assessing heteroscedasticity are also developed based on the modelfitting methods. Such inference procedures are shown to be valid for any unspecified conditional error distribution given factors, and for any factor types including fixed and serially correlated factors;The heteroscedastic factor analysis approach is particularly useful for factor score estimation. Estimators of the factor value for an individual are introduced, and their individual-specific estimated variances are presented. The proposed methods are shown to produce accurate and efficient inferences for underlying factor scores;Large sample theory and comprehensive simulation studies are presented in support of the proposed approach. Some examples of the heteroscedastic factor analysis model and the associated inference methods are illustrated

Reassessing employer expectations of graduates in UK travel services

This article sets out to ascertain travel and tourism industries employers' views on degrees. Research of this kind and on this scale has not previously been carried out and a large scale survey of industry views was conducted with key issues identified and discussed. These cover topics such as the employment of graduates within the UK travel services industry, views on their contribution and appropriateness, the types of skills that such degrees provide, salary scales and graduate training schemes. Current government policy on widening participation in higher education (HE) and its impact on industry skills is also evaluated. The issue of the provision of tourism curricula and their content has at the beginning of 2007 once again been pushed centre stage. This is as a result of the increasing scrutiny of the Sector Skills organisation People 1st and the launch of the government's new vocational diplomas in 2008. The findings in this article are pertinent for government bodies and educators alike and have previously been shared with the Sector Skills organisation and Department of Culture, Media and Sport (DCMS) in addressing HE in tourism

Statistical techniques to construct assays for identifying likely responders to a treatment under evaluation from cell line genomic data

<p>Abstract</p> <p>Background</p> <p>Developing the right drugs for the right patients has become a mantra of drug development. In practice, it is very difficult to identify subsets of patients who will respond to a drug under evaluation. Most of the time, no single diagnostic will be available, and more complex decision rules will be required to define a sensitive population, using, for instance, mRNA expression, protein expression or DNA copy number. Moreover, diagnostic development will often begin with in-vitro cell-line data and a high-dimensional exploratory platform, only later to be transferred to a diagnostic assay for use with patient samples. In this manuscript, we present a novel approach to developing robust genomic predictors that are not only capable of generalizing from in-vitro to patient, but are also amenable to clinically validated assays such as qRT-PCR.</p> <p>Methods</p> <p>Using our approach, we constructed a predictor of sensitivity to dacetuzumab, an investigational drug for CD40-expressing malignancies such as lymphoma using genomic measurements of cell lines treated with dacetuzumab. Additionally, we evaluated several state-of-the-art prediction methods by independently pairing the feature selection and classification components of the predictor. In this way, we constructed several predictors that we validated on an independent DLBCL patient dataset. Similar analyses were performed on genomic measurements of breast cancer cell lines and patients to construct a predictor of estrogen receptor (ER) status.</p> <p>Results</p> <p>The best dacetuzumab sensitivity predictors involved ten or fewer genes and accurately classified lymphoma patients by their survival and known prognostic subtypes. The best ER status classifiers involved one or two genes and led to accurate ER status predictions more than 85% of the time. The novel method we proposed performed as well or better than other methods evaluated.</p> <p>Conclusions</p> <p>We demonstrated the feasibility of combining feature selection techniques with classification methods to develop assays using cell line genomic measurements that performed well in patient data. In both case studies, we constructed parsimonious models that generalized well from cell lines to patients.</p

Strategic innovation through outsourcing:the role of relational and contractual governance

There is growing evidence that client firms expect outsourcing suppliers to transform their business. Indeed, most outsourcing suppliers have delivered IT operational and business process innovation to client firms; however, achieving strategic innovation through outsourcing has been perceived to be far more challenging. Building on the growing interest in the IS outsourcing literature, this paper seeks to advance our understanding of the role that relational and contractual governance plays in achieving strategic innovation through outsourcing. We hypothesized and tested empirically the relationship between the quality of client-supplier relationships and the likelihood of achieving strategic innovation, and the interaction effect of different contract types, such as fixed-price, time and materials, partnership and their combinations. Results from a pan-European survey of 248 large firms suggest that high-quality relationships between clients and suppliers may indeed help achieve strategic innovation through outsourcing. However, within the spectrum of various outsourcing contracts, only the partnership contract, when included in the client contract portfolio alongside either fixed-price, time and materials or their combination, presents a significant positive effect on relational governance and is likely to strengthen the positive effect of the quality of client-supplier relationships on strategic innovation

Phylogeography of Recently Emerged DENV-2 in Southern Viet Nam

Revealing the dispersal of dengue viruses (DENV) in time and space is central to understanding their epidemiology. However, the processes that shape DENV transmission patterns at the scale of local populations are not well understood, particularly the impact of such factors as human population movement and urbanization. Herein, we investigated trends in the spatial dynamics of DENV-2 transmission in the highly endemic setting of southern Viet Nam. Through a phylogeographic analysis of 168 full-length DENV-2 genome sequences obtained from hospitalized dengue cases from 10 provinces in southern Viet Nam, we reveal substantial genetic diversity in both urban and rural areas, with multiple lineages identified in individual provinces within a single season, and indicative of frequent viral migration among communities. Focusing on the recently introduced Asian I genotype, we observed particularly high rates of viral exchange between adjacent geographic areas, and between Ho Chi Minh City, the primary urban center of this region, and populations across southern Viet Nam. Within Ho Chi Minh City, patterns of DENV movement appear consistent with a gravity model of virus dispersal, with viruses traveling across a gradient of population density. Overall, our analysis suggests that Ho Chi Minh City may act as a source population for the dispersal of DENV across southern Viet Nam, and provides further evidence that urban areas of Southeast Asia play a primary role in DENV transmission. However, these data also indicate that more rural areas are also capable of maintaining virus populations and hence fueling DENV evolution over multiple seasons

Simple and Reliable Determination of Intravoxel Incoherent Motion Parameters for the Differential Diagnosis of Head and Neck Tumors

Intravoxel incoherent motion (IVIM) imaging can characterize diffusion and perfusion of normal and diseased tissues, and IVIM parameters are authentically determined by using cumbersome least-squares method. We evaluated a simple technique for the determination of IVIM parameters using geometric analysis of the multiexponential signal decay curve as an alternative to the least-squares method for the diagnosis of head and neck tumors. Pure diffusion coefficients (D), microvascular volume fraction (f), perfusion-related incoherent microcirculation (D), and perfusion parameter that is heavily weighted towards extravascular space (P) were determined geometrically (Geo D, Geo f, and Geo P) or by least-squares method (Fit D, Fit f, and Fit D) in normal structures and 105 head and neck tumors. The IVIM parameters were compared for their levels and diagnostic abilities between the 2 techniques. The IVIM parameters were not able to determine in 14 tumors with the least-squares method alone and in 4 tumors with the geometric and least-squares methods. The geometric IVIM values were significantly different (p<0.001) from Fit values (+2±64% and 7±24% for D and f values, respectively). Geo D and Fit D differentiated between lymphomas and SCCs with similar efficacy (78% and 80% accuracy, respectively). Stepwise approaches using combinations of Geo D and Geo P, Geo D and Geo f, or Fit D and Fit Ddifferentiated between pleomorphic adenomas, Warthin tumors, and malignant salivary gland tumors with the same efficacy (91% accuracy = 21/ 23). However, a stepwise differentiation using Fit D and Fit f was less effective (83% accuracy = 19/23). Considering cumbersome procedures with the least squares method compared with the geometric method, we concluded that the geometric determination of IVIM parameters can be an alternative to least-squares method in the diagnosis of head and neck tumors

Learning environments research in English classrooms

Although learning environments research has thrived for decades in many countries and school subjects, English classroom environment research is still in its infancy. This article paves the way for expanding research on English classroom environments by (1) reviewing the limited past research in English classrooms and (2) reporting the first study of English learning environments in Singaporean primary schools. For a sample of 441 grade 6 students, past research in other subjects was replicated in that a modified version of the What Is Happening In this Class? questionnaire was cross-validated, classroom environment was found to vary with the determinants of student sex and ethnicity, and associations emerged between students’ attitudes and the nature of the classroom environment