Simulation-Based Finite-and Large-sample Inference Methods in Multivariate Regressions and Seemingly Unrelated Regressions

In the context of multivariate regression (MLR) and seemingly unrelated regressions (SURE) models, it is well known that commonly employed asymptotic test criteria are seriously biased towards overrejection. in this paper, we propose finite-and large-sample likelihood-based test procedures for possibly non-linear hypotheses on the coefficients of MLR and SURE systems.

Validierung von HPLC-Methoden zur Bestimmung von Polyphenolen und Carotinoiden in Möhren, Weizen und Mais unterschiedlicher Herkunft

In den vorliegenden Untersuchungen wurde der Gehalt von Carotinoiden in Weizen, Mais und Möhren sowie der Polyphenolgehalt in Möhren mit analytischen Methoden zum Nachweis dieser Substanzen gemessen. Der Gehalt der Carotinoide in Mais und der Gehalt der phenolischen Bestandteile in Möhren wurde mit Messungen mittels HPLC-Analytik gemessen. Die Methoden wurden aus literaturbekannten Verfahren abgeleitet und an die Anforderungen der untersuchten Probenmatrices angepasst und validiert. Dem Verfahren lag die Frage zugrunde, ob es möglich ist, Kulturpflanzen aus verschiedenen Anbausystemen auf der Basis des Gehaltes bestimmter sekundärer Pflanzeninhaltsstoffe zu differenzieren und aufgrund von Unterschieden im Gehalt der sekundären Pflanzeninhaltsstoffe zu klassifizieren. Die Gesamtverfahren wurden dabei gemäß der ISO 17025 validiert. Für die Messungen standen Proben aus definierten Langzeitversuchen und Erzeugerproben ausgesuchter ökologisch bzw. konventionell arbeitender Anbaubetriebe zur Verfügung. Als Grundlage für eine valide Methodeneinschätzung wurden die Messungen an codierten Proben vorgenommen. Eine Decodierung der Proben erfolgte erst nach der Vorlage der Messergebnisse in den genannten Projekten. Die Messung und Auswertung des Carotinoidgehaltes in Weizen, Mais und Möhren vor dem Hintergrund der Differenzierung und Klassifizierung erfolgte in Proben eines Erntejahres. Die Messung des Gehaltes phenolischer Substanzen in Möhren erfolgte in Möhren aus 3 Erntejahren. Die verwendeten HPLC-Verfahren konnten in Bezug auf den analytischen Teil der Messungen in den einzelnen Verfahrensschritten Linearität, Spezifität, Präzision und Robustheit erfolgreich überprüft werden. Darüber hinaus wurden wichtige Einflussgrößen auf die Messungen bestimmt. Für die Verfahren zur photometrischen Bestimmung der Gesamtcarotinoide konnte eine Grundkalibrierung der Parameter Präzision und Linearität des Verfahrens erfolgreich durchgeführt werden. Während der Anwendung der HPLC-Methoden an codierten Proben konnten in allen untersuchten Probenmatrices quantitativ bedeutende Inhaltsstoffe nachgewiesen und identifiziert werden. Eine vollständige Identifizierung aller dargestellten Peaks konnte in den Untersuchungen der Polyphenole in Möhren und der Carotinoide in Mais nicht erfolgen. Im Hinblick auf die Frage nach der Differenzierung und Klassifizierung ergab sich in den verschiedenen Proben ein unterschiedliches Bild. Sowohl durch den Carotinoid- als auch den Polyphenolgehalt konnten einzelne Proben statistisch signifikant differenziert werden. Die Trennleistung hing dabei sowohl von den jeweiligen Komponenten als auch von der untersuchten Probenmatrix ab. Ein durchgängig höherer Gehalt sekundärer Pflanzeninhaltsstoffe in Proben aus ökologischem Anbau konnte nicht bestätigt werden. Für die Klassifizierung der Proben verschiedener Anbauvarianten und konnten multivariate statistische Methoden, wie lineare Diskriminantenanalyse (LDA) und Classification and Regression Tree (CART), erfolgreich angewandt werden. Eine Klassifizierung mit unterschiedlichen statistischen Verfahren erbrachte dabei unterschiedliche Ergebnisse. In der Klassifizierung der decodierten Proben mittels LDA wirkten sich die Faktoren Sorte und Standort stärker auf das Klassifizierungsergebnis aus als der Faktor Anbausystem. Eine Klassifizierung der decodierten Proben nach dem Anbausystem wurde mit dem CART-Verfahren durchgeführt. Auf dieser Basis wurden für die Polyphenole in Möhren 97 % der Proben richtig klassifiziert. Durch die Messwerte des Carotinoidgehaltes und des Luteingehaltes in Weizen konnte der größere Teil der Proben (90 %) korrekt klassifiziert werden. Auf der Basis des Carotinoidgehaltes in Mais wurde der Großteil der Proben (95 %) korrekt nach dem Anbausystem klassifiziert. Auf der Basis des mittels HPLC gemessenen Carotinoidgehaltes in Möhren konnten die Proben 97 % korrekt klassifiziert werden (97 %). Insgesamt erscheint der Grundgedanke der Klassifizierung durch den Gehalt sekundärer Pflanzeninhaltsstoffe vielversprechend. Durch die vielfältigen Einflussgrößen auf den Sekundärstoffwechsel von Pflanzen müssten Veränderungen, die durch Sorte und Standort auftreten, über mehrere Jahre erhoben und systematisiert werden.

Enfermedad tiroidea autoinmune en pacientes colombianos con lupus eritematoso sistémico

Objetivos: Determinar la prevalencia y los factores asociados con el desarrollo de hipotiroidismo autoinmune (HA) en una cohorte de pacientes con lupus eritematoso sistémico (LES), y analizar la información actual en cuanto a la prevalencia e impacto de la enfermedad tiroidea autoinmune y la autoinmunidad tiroidea en pacientes con LES. Métodos: Este fue un estudio realizado en dos pasos. Primero, un total de 376 pacientes con LES fueron evaluados sistemáticamente por la presencia de: 1) HA confirmado, 2) positividad para anticuerpos tiroperoxidasa/tiroglobulina (TPOAb/TgAb) sin hipotiroidismo, 3) hipotiroidismo no autoinmune, y 4) pacientes con LES sin hipotiroidismo ni positividad para TPOAb/TgAb. Se construyeron modelos multivariados y árboles de regresión y clasificación para analizar los datos. Segundo, la información actual fue evaluada a través de una revisión sistemática de la literatura (RLS). Se siguieron las guías PRISMA para la búsqueda en las bases de datos PubMed, Scopus, SciELO y Librería Virtual en Salud. Resultados: En nuestra cohorte, la prevalencia de HA confirmado fue de 12% (Grupo 1). Sin embargo, la frecuencia de positividad para TPOAb y TgAb fue de 21% y 10%, respectivamente (Grupo 2). Los pacientes con LES sin HA, hipotiroidismo no autoinmune ni positividad para TPOAb/TgAb constituyeron el 40% de la corhorte. Los pacientes con HA confirmada fueron estadísticamente significativo de mayor edad y tuvieron un inicio tardío de la enfermedad. El tabaquismo (ORA 6.93, IC 95% 1.98-28.54, p= 0.004), la presencia de Síndrome de Sjögren (SS) (ORA 23.2, IC 95% 1.89-359.53, p= 0.015) y la positividad para anticuerpos anti-péptido cíclico citrulinado (anti-CCP) (ORA 10.35, IC 95% 1.04-121.26, p= 0.047) se asociaron con la coexistencia de LES-HA, ajustado por género y duración de la enfermedad. El tabaquismo y el SS fueron confirmados como factores predictivos para LES-HA (AUC del modelo CART = 0.72). En la RSL, la prevalencia de ETA en LES varío entre 1% al 60%. Los factores asociados con esta poliautoinmunidad fueron el género femenino, edad avanzada, tabaquismo, positividad para algunos anticuerpos, SS y el compromiso articular y cutáneo. Conclusiones: La ETA es frecuente en pacientes con LES, y no afecta la severidad del LES. Los factores de riesgo identificados ayudarán a los clínicos en la búsqueda de ETA. Nuestros resultados deben estimular políticas para la suspensión del tabaquismo en pacientes con LES.

A multivariate ultrastructural errors-in-variables model with equation error

This paper deals with asymptotic results on a multivariate ultrastructural errors-in-variables regression model with equation errors Sufficient conditions for attaining consistent estimators for model parameters are presented Asymptotic distributions for the line regression estimators are derived Applications to the elliptical class of distributions with two error assumptions are presented The model generalizes previous results aimed at univariate scenarios (C) 2010 Elsevier Inc All rights reserved

Improved maximum-likelihood estimation in a regression model with general parametrization

We analyse the finite-sample behaviour of two second-order bias-corrected alternatives to the maximum-likelihood estimator of the parameters in a multivariate normal regression model with general parametrization proposed by Patriota and Lemonte [A. G. Patriota and A. J. Lemonte, Bias correction in a multivariate regression model with genereal parameterization, Stat. Prob. Lett. 79 (2009), pp. 1655-1662]. The two finite-sample corrections we consider are the conventional second-order bias-corrected estimator and the bootstrap bias correction. We present the numerical results comparing the performance of these estimators. Our results reveal that analytical bias correction outperforms numerical bias corrections obtained from bootstrapping schemes.

Tree-structured smooth transition models

The goal of this paper is to introduce a class of tree-structured models that combines aspects of regression trees and smooth transition regression models. The model is called the Smooth Transition Regression Tree (STR-Tree). The main idea relies on specifying a multiple-regime parametric model through a tree-growing procedure with smooth transitions among different regimes. Decisions about splits are entirely based on a sequence of Lagrange Multiplier (LM) tests of hypotheses.

Predicting smear negative pulmonary tuberculosis with classification trees and logistic regression: a cross-sectional study

Abstract Background Smear negative pulmonary tuberculosis (SNPT) accounts for 30% of pulmonary tuberculosis cases reported yearly in Brazil. This study aimed to develop a prediction model for SNPT for outpatients in areas with scarce resources. Methods The study enrolled 551 patients with clinical-radiological suspicion of SNPT, in Rio de Janeiro, Brazil. The original data was divided into two equivalent samples for generation and validation of the prediction models. Symptoms, physical signs and chest X-rays were used for constructing logistic regression and classification and regression tree models. From the logistic regression, we generated a clinical and radiological prediction score. The area under the receiver operator characteristic curve, sensitivity, and specificity were used to evaluate the model's performance in both generation and validation samples. Results It was possible to generate predictive models for SNPT with sensitivity ranging from 64% to 71% and specificity ranging from 58% to 76%. Conclusion The results suggest that those models might be useful as screening tools for estimating the risk of SNPT, optimizing the utilization of more expensive tests, and avoiding costs of unnecessary anti-tuberculosis treatment. Those models might be cost-effective tools in a health care network with hierarchical distribution of scarce resources.

Table 1: Soil chemical properties of the analysed depth profiles in the Venice lagoon

Visual traces of iron reduction and oxidation are linked to the redox status of soils and have been used to characterise the quality of agricultural soils.We tested whether this feature could also be used to explain the spatial pattern of the natural vegetation of tidal habitats. If so, an easy assessment of the effect of rising sea level on tidal ecosystems would be possible. Our study was conducted at the salt marshes of the northern lagoon of Venice, which are strongly threatened by erosion and rising sea level and are part of the world heritage 'Venice and its lagoon'. We analysed the abundance of plant species at 255 sampling points along a land-sea gradient. In addition, we surveyed the redox morphology (presence/absence of red iron oxide mottles in the greyish topsoil horizons) of the soils and the presence of disturbances. We used indicator species analysis, correlation trees and multivariate regression trees to analyse relations between soil properties and plant species distribution. Plant species with known sensitivity to anaerobic conditions (e.g. Halimione portulacoides) were identified as indicators for oxic soils (showing iron oxide mottles within a greyish soil matrix). Plant species that tolerate a low redox potential (e.g. Spartina maritima) were identified as indicators for anoxic soils (greyish matrix without oxide mottles). Correlation trees and multivariate regression trees indicate the dominant role of the redox morphology of the soils in plant species distribution. In addition, the distance from the mainland and the presence of disturbances were identified as tree-splitting variables. The small-scale variation of oxygen availability plays a key role for the biodiversity of salt marsh ecosystems. Our results suggest that the redox morphology of salt marsh soils indicates the plant availability of oxygen. Thus, the consideration of this indicator may enable an understanding of the heterogeneity of biological processes in oxygen-limited systems and may be a sensitive and easy-to-use tool to assess human impacts on salt marsh ecosystems.

A fuzzy decision tree-based duration model for Standard Yorùbá text-to-speech synthesis

In this paper, we present syllable-based duration modelling in the context of a prosody model for Standard Yorùbá (SY) text-to-speech (TTS) synthesis applications. Our prosody model is conceptualised around a modular holistic framework. This framework is implemented using the Relational Tree (R-Tree) techniques. An important feature of our R-Tree framework is its flexibility in that it facilitates the independent implementation of the different dimensions of prosody, i.e. duration, intonation, and intensity, using different techniques and their subsequent integration. We applied the Fuzzy Decision Tree (FDT) technique to model the duration dimension. In order to evaluate the effectiveness of FDT in duration modelling, we have also developed a Classification And Regression Tree (CART) based duration model using the same speech data. Each of these models was integrated into our R-Tree based prosody model. We performed both quantitative (i.e. Root Mean Square Error (RMSE) and Correlation (Corr)) and qualitative (i.e. intelligibility and naturalness) evaluations on the two duration models. The results show that CART models the training data more accurately than FDT. The FDT model, however, shows a better ability to extrapolate from the training data since it achieved a better accuracy for the test data set. Our qualitative evaluation results show that our FDT model produces synthesised speech that is perceived to be more natural than our CART model. In addition, we also observed that the expressiveness of FDT is much better than that of CART. That is because the representation in FDT is not restricted to a set of piece-wise or discrete constant approximation. We, therefore, conclude that the FDT approach is a practical approach for duration modelling in SY TTS applications. © 2006 Elsevier Ltd. All rights reserved.

Breastfeeding experiences of Japanese women living in Perth, Australia

The aim of this study was to document the breastfeeding practices of Japanese-Australian mothers living in Perth. A cross-sectional survey of mothers who had delivered babies in Japan or Australia or both was carried out on a sample of 163 mothers recruited through Japanese social and cultural groups in Perth and by a 'snowball' technique. Factors involved in the decision to breastfeed were analysed using multivariate regression analysis. The main outcome measures were the initiation and duration of breastfeeding and cultural beliefs about breastfeeding. Breastfeeding initiation rates of the Japanese- Australian mothers in Japan and in Australia were higher than for other Australians and are consistent with breastfeeding rates in Japan. In Australia, 65% of Japanese-Australian mothers were still breastfeeding at six months. The most common reason for the decision to cease breastfeeding was 'insufficient breastmilk'. The significant factors in breastfeeding duration were 'the time the infant was introduced to infant formula', 'the time when the feeding decision was made', 'doctors support breastfeeding' and 'the mother received enough help from hospital staff'; these were positively associated with the duration of breastfeeding. Japanese mothers take a lot of notice of advice given by health professionals about infant feeding practices.

Spatial analysis of notified cryptosporidiosis infections in Brisbane, Australia

Purpose: This study explored the spatial distribution of notified cryptosporidiosis cases and identified major socioeconomic factors associated with the transmission of cryptosporidiosis in Brisbane, Australia. Methods: We obtained the computerized data sets on the notified cryptosporidiosis cases and their key socioeconomic factors by statistical local area (SLA) in Brisbane for the period of 1996 to 2004 from the Queensland Department of Health and Australian Bureau of Statistics, respectively. We used spatial empirical Bayes rates smoothing to estimate the spatial distribution of cryptosporidiosis cases. A spatial classification and regression tree (CART) model was developed to explore the relationship between socioeconomic factors and the incidence rates of cryptosporidiosis. Results: Spatial empirical Bayes analysis reveals that the cryptosporidiosis infections were primarily concentrated in the northwest and southeast of Brisbane. A spatial CART model shows that the relative risk for cryptosporidiosis transmission was 2.4 when the value of the social economic index for areas (SEIFA) was over 1028 and the proportion of residents with low educational attainment in an SLA exceeded 8.8%. Conclusions: There was remarkable variation in spatial distribution of cryptosporidiosis infections in Brisbane. Spatial pattern of cryptosporidiosis seems to be associated with SEIFA and the proportion of residents with low education attainment.

Depression, anxiety and body image after treatment for invasive stage one epithelial ovarian cancer

Background: Diagnosis of epithelial ovarian cancer (EOC) in young women has major implications including those to their reproductive potential. We evaluated depression, anxiety and body image in patients with stage I EOC treated with fertility sparing surgery (FSS) or radical surgery (RS). We also investigated fertility outcomes after FSS.----- Methods: A retrospective study was undertaken in which 62 patients completed questionnaires related to anxiety, depression, body image and fertility outcomes. Additional information on adjuvant therapy after FSS and RS and demographic details were abstracted from medical records. Both bi and multivariate regression models were used to assess the relationship between demographic, clinical and pathological results and scores for anxiety, depression and body image.----- Results: Thirty-nine patients underwent RS and the rest, FSS. The percentage of patients reporting elevated anxiety and depression (subscores ≥ 11) were 27 % and 5% respectively. The median (inter quartile range) score for body image scale (BIS) was 6 (3-15). None of the demographic or clinical factors examined showed significant association with anxiety and BIS with the exception of ‘time since diagnosis’. For depression, post-menopausal status was the only independent predictor. Among those 23 patients treated by FSS, 14 patients tried to conceive (7 successful), resulting in 7 live births, one termination of pregnancy and one miscarriage.----- Conclusion: This study shows that psychological issues are common in women treated for stage I EOC. Reproduction after FSS is feasible and lead to the birth of healthy babies in about half of patients who wished to have another child. Further prospective studies with standardised instruments are required.

Digital kids, analogue students : a mixed methods study of students' engagement with a school-based Web 2.0 learning innovation

The inquiry documented in this thesis is located at the nexus of technological innovation and traditional schooling. As we enter the second decade of a new century, few would argue against the increasingly urgent need to integrate digital literacies with traditional academic knowledge. Yet, despite substantial investments from governments and businesses, the adoption and diffusion of contemporary digital tools in formal schooling remain sluggish. To date, research on technology adoption in schools tends to take a deficit perspective of schools and teachers, with the lack of resources and teacher ‘technophobia’ most commonly cited as barriers to digital uptake. Corresponding interventions that focus on increasing funding and upskilling teachers, however, have made little difference to adoption trends in the last decade. Empirical evidence that explicates the cultural and pedagogical complexities of innovation diffusion within long-established conventions of mainstream schooling, particularly from the standpoint of students, is wanting. To address this knowledge gap, this thesis inquires into how students evaluate and account for the constraints and affordances of contemporary digital tools when they engage with them as part of their conventional schooling. It documents the attempted integration of a student-led Web 2.0 learning initiative, known as the Student Media Centre (SMC), into the schooling practices of a long-established, high-performing independent senior boys’ school in urban Australia. The study employed an ‘explanatory’ two-phase research design (Creswell, 2003) that combined complementary quantitative and qualitative methods to achieve both breadth of measurement and richness of characterisation. In the initial quantitative phase, a self-reported questionnaire was administered to the senior school student population to determine adoption trends and predictors of SMC usage (N=481). Measurement constructs included individual learning dispositions (learning and performance goals, cognitive playfulness and personal innovativeness), as well as social and technological variables (peer support, perceived usefulness and ease of use). Incremental predictive models of SMC usage were conducted using Classification and Regression Tree (CART) modelling: (i) individual-level predictors, (ii) individual and social predictors, and (iii) individual, social and technological predictors. Peer support emerged as the best predictor of SMC usage. Other salient predictors include perceived ease of use and usefulness, cognitive playfulness and learning goals. On the whole, an overwhelming proportion of students reported low usage levels, low perceived usefulness and a lack of peer support for engaging with the digital learning initiative. The small minority of frequent users reported having high levels of peer support and robust learning goal orientations, rather than being predominantly driven by performance goals. These findings indicate that tensions around social validation, digital learning and academic performance pressures influence students’ engagement with the Web 2.0 learning initiative. The qualitative phase that followed provided insights into these tensions by shifting the analytics from individual attitudes and behaviours to shared social and cultural reasoning practices that explain students’ engagement with the innovation. Six indepth focus groups, comprising 60 students with different levels of SMC usage, were conducted, audio-recorded and transcribed. Textual data were analysed using Membership Categorisation Analysis. Students’ accounts converged around a key proposition. The Web 2.0 learning initiative was useful-in-principle but useless-in-practice. While students endorsed the usefulness of the SMC for enhancing multimodal engagement, extending peer-topeer networks and acquiring real-world skills, they also called attention to a number of constraints that obfuscated the realisation of these design affordances in practice. These constraints were cast in terms of three binary formulations of social and cultural imperatives at play within the school: (i) ‘cool/uncool’, (ii) ‘dominant staff/compliant student’, and (iii) ‘digital learning/academic performance’. The first formulation foregrounds the social stigma of the SMC among peers and its resultant lack of positive network benefits. The second relates to students’ perception of the school culture as authoritarian and punitive with adverse effects on the very student agency required to drive the innovation. The third points to academic performance pressures in a crowded curriculum with tight timelines. Taken together, findings from both phases of the study provide the following key insights. First, students endorsed the learning affordances of contemporary digital tools such as the SMC for enhancing their current schooling practices. For the majority of students, however, these learning affordances were overshadowed by the performative demands of schooling, both social and academic. The student participants saw engagement with the SMC in-school as distinct from, even oppositional to, the conventional social and academic performance indicators of schooling, namely (i) being ‘cool’ (or at least ‘not uncool’), (ii) sufficiently ‘compliant’, and (iii) achieving good academic grades. Their reasoned response therefore, was simply to resist engagement with the digital learning innovation. Second, a small minority of students seemed dispositionally inclined to negotiate the learning affordances and performance constraints of digital learning and traditional schooling more effectively than others. These students were able to engage more frequently and meaningfully with the SMC in school. Their ability to adapt and traverse seemingly incommensurate social and institutional identities and norms is theorised as cultural agility – a dispositional construct that comprises personal innovativeness, cognitive playfulness and learning goals orientation. The logic then is ‘both and’ rather than ‘either or’ for these individuals with a capacity to accommodate both learning and performance in school, whether in terms of digital engagement and academic excellence, or successful brokerage across multiple social identities and institutional affiliations within the school. In sum, this study takes us beyond the familiar terrain of deficit discourses that tend to blame institutional conservatism, lack of resourcing and teacher resistance for low uptake of digital technologies in schools. It does so by providing an empirical base for the development of a ‘third way’ of theorising technological and pedagogical innovation in schools, one which is more informed by students as critical stakeholders and thus more relevant to the lived culture within the school, and its complex relationship to students’ lives outside of school. It is in this relationship that we find an explanation for how these individuals can, at the one time, be digital kids and analogue students.

The role of social capital in reducing negative health outcomes among police officers

This paper investigates the role of social capital on the reduction of short and long run negative health effects associated with stress, as well as indicators of burnout among police officers. Despite the large volume of research on either social capital or the health effects of stress, the interaction of these factors remains an underexplored topic. In this empirical analysis we aim to reduce such a shortcoming focusing on a highly stressful and emotionally draining work environment, namely law enforcement agents who perform as an essential part of maintaining modern society. Using a multivariate regression analysis focusing on three different proxies of health and three proxies for social capital conducting also several robustness checks, we find strong evidence that increased levels of social capital is highly correlated with better health outcomes. Additionally we observe that while social capital at work is very important, social capital in the home environment and work-life balance are even more important. From a policy perspective, our findings suggest that work and stress programs should actively encourage employees to build stronger social networks as well as incorporate better working/home life arrangements.

Evaluation of risk factors leading to cost overrun in delivery of highway construction projects

Accurate owner budget estimates are critical to the initial decision-to-build process for highway construction projects. However, transportation projects have historically experienced significant construction cost overruns from the time the decision to build has been taken by the owner. This paper addresses the problem of why highway projects overrun their predicted costs. It identifies the owner risk variables that contribute to significant cost overrun and then uses factor analysis, expert elicitation, and the nominal group technique to establish groups of importance ranked owner risks. Stepwise multivariate regression analysis is also used to investigate any correlation of the percentage of cost overrun with risks, together with attributes such as highway project type, indexed cost, geographics location, and project delivery method. The research results indicate a correlation between the reciprocal of project budgets size and percentage cost overrun. This can be useful for owners in determining more realistic decision-to-build highway budget estimates by taking into account the economies of scale associated with larger projects.