105 resultados para posterior predictive check


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One of the fundamental econometric models in finance is predictive regression. The standard least squares method produces biased coefficient estimates when the regressor is persistent and its innovations are correlated with those of the dependent variable. This article proposes a general and convenient method based on the jackknife technique to tackle the estimation problem. The proposed method reduces the bias for both single- and multiple-regressor models and for both short- and long-horizon regressions. The effectiveness of the proposed method is demonstrated by simulations. An empirical application to equity premium prediction using the dividend yield and the short rate highlights the differences between the results by the standard approach and those by the bias-reduced estimator. The significant predictive variables under the ordinary least squares become insignificant after adjusting for the finite-sample bias. These discrepancies suggest that bias reduction in predictive regressions is important in practical applications.

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Over the last few decades, construction project performance has been evaluated due to the increase of delays, cost overruns and quality failures. Growing numbers of disputes, inharmonious working environments, conflict, blame cultures, and mismatches of objectives among project teams have been found to be contributory factors to poor project performance. Performance measurement (PM) approaches have been developed to overcome these issues, however, the comprehensiveness of PM as an overall approach is still criticised in terms of the iron triangle; namely time, cost, and quality. PM has primarily focused on objective measures, however, continuous improvement requires the inclusion of subjective measures, particularly contractor satisfaction (Co-S). It is challenging to deal with the two different groups of large and small-medium contractor satisfaction as to date, Co-S has not been extensively defined, primarily in developing countries such as Malaysia. Therefore, a Co-S model is developed in this research which aims to fulfil the current needs in the construction industry by integrating performance measures to address large and small-medium contractor perceptions. The positivist paradigm used in the research was adhered to by reviewing relevant literature and evaluating expert discussions on the research topic. It yielded a basis for the contractor satisfaction model (CoSMo) development which consists of three elements: contractor satisfaction (Co-S) dimensions; contributory factors and characteristics (project and participant). Using valid questionnaire results from 136 contractors in Malaysia lead to the prediction of several key factors of contractor satisfaction and to an examination of the relationships between elements. The relationships were examined through a series of sequential statistical analyses, namely correlation, one-way analysis of variance (ANOVA), t-tests and multiple regression analysis (MRA). Forward and backward MRAs were used to develop Co-S mathematical models. Sixteen Co-S models were developed for both large and small-medium contractors. These determined that the large contractor Malaysian Co-S was most affected by the conciseness of project scope and quality of the project brief. Contrastingly, Co-S for small-medium contractors was strongly affected by the efficiency of risk control in a project. The results of the research provide empirical evidence in support of the notion that appropriate communication systems in projects negatively contributes to large Co-S with respect to cost and profitability. The uniqueness of several Co-S predictors was also identified through a series of analyses on small-medium contractors. These contractors appear to be less satisfied than large contractors when participants lack effectiveness in timely authoritative decision-making and communication between project team members. Interestingly, the empirical results show that effective project health and safety measures are influencing factors in satisfying both large and small-medium contractors. The perspectives of large and small-medium contractors in respect to the performance of the entire project development were derived from the Co-S models. These were statistically validated and refined before a new Co-S model was developed. Developing such a unique model has the potential to increase project value and benefit all project participants. It is important to improve participant collaboration as it leads to better project performance. This study may encourage key project participants; such as client, consultant, subcontractor and supplier; to increase their attention to contractor needs in the development of a project. Recommendations for future research include investigating other participants‟ perspectives on CoSMo and the impact of the implementation of CoSMo in a project, since this study is focused purely on the contractor perspective.

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The role of individual ocular tissues in mediating changes to the sclera during myopia development is unclear. The aim of this study was to examine the effects of retina, RPE and choroidal tissues from myopic and hyperopic chick eyes on the DNA and glycosaminoglycan (GAG) content in cultures of chick scleral fibroblasts. Primary cultures of fibroblastic cells expressing vimentin and -smooth muscle actin were established in serum-supplemented growth medium from 8-day-old normal chick sclera. The fibroblasts were subsequently co-cultured with posterior eye cup tissue (full thickness containing retina, RPE and choroid) obtained from untreated eyes and eyes wearing translucent diffusers (form-deprivation myopia, FDM) or -15D lenses (lens-induced myopia, LIM) for 3 days (post hatch day 5 to 8) (n=6 per treatment group). The effect of tissues (full thickness and individual retina, RPE, and choroid layers) from -15D (LIM) versus +15D (lens-induced hyperopia, LIH) treated eyes was also determined. Refraction changes in the direction predicted by the visual treatments were confirmed by retinoscopy prior to tissue collection. Glycosaminoglycan (GAG) and DNA content of the scleral fibroblast cultures were measured using GAG and PicoGreen assays. There was no significant difference in the effect of full thickness tissue from either FDM or LIM treated eyes on DNA and GAG content of scleral fibroblasts (DNA 8.9±2.6 µg and 8.4±1.1 µg, p=0.12; GAG 11.2±0.6 µg and 10.1±1.0 µg, p=0.34). Retina from LIM eyes did not alter fibroblast DNA or GAG content compared to retina from LIH eyes (DNA 27.2±1.7 µg versus 23.2±1.5 µg, p=0.21; GAG 28.1±1.7 µg versus. 28.7±1.2 µg, p=0.46). Similarly, the choroid from LIH and LIM eyes did not produce a differential effect on DNA content (DNA, LIM 46.9±6.4 versus LIH 51.5±4.7 µg, p=0.31), whereas GAG content was higher for cells in co-culture with choroid from LIH eyes (GAG 32.5±0.7 µg versus 18.9±1.2 µg, F1,6=9.210, p=0.0002). In contrast, fibroblast DNA was greater in co-culture with RPE from LIM eyes than the empty basket and DNA content less for co-culture with RPE from LIH eyes (LIM: 72.4±6.3 µg versus Empty basket: 46.03±1.0 µg; F1,6=69.99, p=0.0005 and LIH: 27.9±2.3 µg versus empty basket: 46.03±1.0 µg; p=0.0004). GAG content was higher with RPE from LIH eyes (LIH: 33.7±1.9 µg versus empty basket: 29.5±0.8 µg, F1,6=13.99, p=0.010) and lower with RPE from LIM eyes (LIM: 27.7±0.9 µg versus empty basket: 29.5±0.8 µg, p=0.021). GAG content of cells in co-culture with choroid from LIH eyes was higher compared to co-culture with choroid from LIM eyes (32.5±0.7 µg versus 18.9±1.2 µg respectively, F1,6=9.210, p=0.0002). In conclusion, these experiments provide evidence for a directional growth signal that is present (and remains) in the ex-vivo RPE, but that does not remain in the ex-vivo retina. The identity of this factor(s) that can modify scleral cell DNA and GAG content requires further research.

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Abstract Background The quantum increases in home Internet access and available online health information with limited control over information quality highlight the necessity of exploring decision making processes in accessing and using online information, specifically in relation to children who do not make their health decisions. Objectives To understand the processes explaining parents’ decisions to use online health information for child health care. Methods Parents (N = 391) completed an initial questionnaire assessing the theory of planned behaviour constructs of attitude, subjective norm, and perceived behavioural control, as well as perceived risk, group norm, and additional demographic factors. Two months later, 187 parents completed a follow-up questionnaire assessing their decisions to use online information for their child’s health care, specifically to 1) diagnose and/or treat their child’s suspected medical condition/illness and 2) increase understanding about a diagnosis or treatment recommended by a health professional. Results Hierarchical multiple regression showed that, for both behaviours, attitude, subjective norm, perceived behavioural control, (less) perceived risk, group norm, and (non) medical background were the significant predictors of intention. For parents’ use of online child health information, for both behaviours, intention was the sole significant predictor of behaviour. The findings explain 77% of the variance in parents’ intention to treat/diagnose a child health problem and 74% of the variance in their intentions to increase their understanding about child health concerns. Conclusions Understanding parents’ socio-cognitive processes that guide their use of online information for child health care is important given the increase in Internet usage and the sometimes-questionable quality of health information provided online. Findings highlight parents’ thirst for information; there is an urgent need for health professionals to provide parents with evidence-based child health websites in addition to general population education on how to evaluate the quality of online health information.

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The current study examined the structure of the volunteer functions inventory within a sample of older individuals (N = 187). The career items were replaced with items examining the concept of continuity of work, a potentially more useful and relevant concept for this population. Factor analysis supported a four factor solution, with values, social and continuity emerging as single factors and enhancement and protective items loading together on a single factor. Understanding items did not load highly on any factor. The values and continuity functions were the only dimensions to emerge as predictors of intention to volunteer. This research has important implications for understanding the motivation of older adults to engage in contemporary volunteering settings.

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This paper presents practical vision-based collision avoidance for objects approximating a single point feature. Using a spherical camera model, a visual predictive control scheme guides the aircraft around the object along a conical spiral trajectory. Visibility, state and control constraints are considered explicitly in the controller design by combining image and vehicle dynamics in the process model, and solving the nonlinear optimization problem over the resulting state space. Importantly, range is not required. Instead, the principles of conical spiral motion are used to design an objective function that simultaneously guides the aircraft along the avoidance trajectory, whilst providing an indication of the appropriate point to stop the spiral behaviour. Our approach is aimed at providing a potential solution to the See and Avoid problem for unmanned aircraft and is demonstrated through a series.

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Constructing train schedules is vital in railways. This complex and time consuming task is however made more difficult by additional requirements to make train schedules robust to delays and other disruptions. For a timetable to be regarded as robust, it should be insensitive to delays of a specified level and its performance with respect to a given metric, should be within given tolerances. In other words the effect of delays should be identifiable and should be shown to be minimal. To this end, a sensitivity analysis is proposed that identifies affected operations. More specifically a sensitivity analysis for determining what operation delays cause each operation to be affected is proposed. The information provided by this analysis gives another measure of timetable robustness and also provides control information that can be used when delays occur in practice. Several algorithms are proposed to identify this information and they utilise a disjunctive graph model of train operations. Upon completion the sets of affected operations can also be used to define the impact of all delays without further disjunctive graph evaluations.

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Introduction This study reports on the application of the Manchester Driver Behaviour Questionnaire (DBQ) to examine the self-reported driving behaviours (e.g., speeding, errors & aggressive manoeuvres) and predict crash involvement among a sample of general Queensland motorists. Material and Methods Surveys were completed by 249 general motorists on-line or via a pen-and-paper format. Results A factor analysis revealed a three factor solution for the DBQ which was consistent with previous Australian-based research. It accounted for 40.5% of the total variance, although some cross-loadings were observed on nine of the twenty items. The internal reliability of the DBQ was satisfactory. However, multivariate analysis using the DBQ revealed little predictive ability of the tool to predict crash involvement or demerit point loss e.g. violation notices. Rather, exposure to the road was found to be predictive of crashes, although speeding did make a small contribution to those who recently received a violation notice. Conclusions Taken together, the findings contribute to a growing body of research that raises questions about the predictive ability of the most widely used driving assessment tool globally. Ongoing research (which also includes official crash and offence outcomes) is required to better understand the actual contribution that the DBQ can make to understanding and improving road safety. Future research should also aim to confirm whether this lack of predictive efficacy originates from broader issues inherent within self-report data (e.g., memory recall problems) or issues underpinning the conceptualisation of the scale.

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Utility functions in Bayesian experimental design are usually based on the posterior distribution. When the posterior is found by simulation, it must be sampled from for each future data set drawn from the prior predictive distribution. Many thousands of posterior distributions are often required. A popular technique in the Bayesian experimental design literature to rapidly obtain samples from the posterior is importance sampling, using the prior as the importance distribution. However, importance sampling will tend to break down if there is a reasonable number of experimental observations and/or the model parameter is high dimensional. In this paper we explore the use of Laplace approximations in the design setting to overcome this drawback. Furthermore, we consider using the Laplace approximation to form the importance distribution to obtain a more efficient importance distribution than the prior. The methodology is motivated by a pharmacokinetic study which investigates the effect of extracorporeal membrane oxygenation on the pharmacokinetics of antibiotics in sheep. The design problem is to find 10 near optimal plasma sampling times which produce precise estimates of pharmacokinetic model parameters/measures of interest. We consider several different utility functions of interest in these studies, which involve the posterior distribution of parameter functions.

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Background: There is currently no early predictive marker of survival for patients receiving chemotherapy for malignant pleural mesothelioma (MPM). Tumour response may be predictive for overall survival (OS), though this has not been explored. We have thus undertaken a combined-analysis of OS, from a 42 day landmark, of 526 patients receiving systemic therapy for MPM. We also validate published progression-free survival rates (PFSRs) and a progression-free survival (PFS) prognostic-index model. Methods: Analyses included nine MPM clinical trials incorporating six European Organisation for Research and Treatment of Cancer (EORTC) studies. Analysis of OS from landmark (from day 42 post-treatment) was considered regarding tumour response. PFSR analysis data included six non-EORTC MPM clinical trials. Prognostic index validation was performed on one non-EORTC data-set, with available survival data. Results: Median OS, from landmark, of patients with partial response (PR) was 12·8 months, stable disease (SD), 9·4 months and progressive disease (PD), 3·4 months. Both PR and SD were associated with longer OS from landmark compared with disease progression (both p < 0·0001). PFSRs for platinum-based combination therapies were consistent with published significant clinical activity ranges. Effective separation between PFS and OS curves provided a validation of the EORTC prognostic model, based on histology, stage and performance status. Conclusion: Response to chemotherapy is associated with significantly longer OS from landmark in patients with MPM. © 2012 Elsevier Ltd. All rights reserved.

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The reversible posterior leukoencephalopathy syndrome (RPLES) is a condition characterised by reversible neurological and radiological findings that has been associated with use of immunosuppressive, chemotherapeutic and more recently novel targeted therapies. We describe the case of a 50-year-old woman with advanced non-small cell lung cancer who developed status epilepticus shortly after receiving cisplatin and gemcitabine chemotherapy. The clinical, radiological and EEG findings during and post event are presented and are in keeping with a diagnosis of RPLES. Early recognition of this rare syndrome, supportive management and withdrawal of the offending agent appear to result in a reversal of the manifestations described. © 2007 Elsevier Ireland Ltd. All rights reserved.

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"One of the more spirited discussions of the first week of this federal election campaign has concerned whether News Corp Australia, as our largest print media company, has a vested interest in the election outcome..."--publisher website

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Sustainability is a key driver for decisions in the management and future development of industries. The World Commission on Environment and Development (WCED, 1987) outlined imperatives which need to be met for environmental, economic and social sustainability. Development of strategies for measuring and improving sustainability in and across these domains, however, has been hindered by intense debate between advocates for one approach fearing that efforts by those who advocate for another could have unintended adverse impacts. Studies attempting to compare the sustainability performance of countries and industries have also found ratings of performance quite variable depending on the sustainability indices used. Quantifying and comparing the sustainability of industries across the triple bottom line of economy, environment and social impact continues to be problematic. Using the Australian dairy industry as a case study, a Sustainability Scorecard, developed as a Bayesian network model, is proposed as an adaptable tool to enable informed assessment, dialogue and negotiation of strategies at a global level as well as being suitable for developing local solutions.

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This paper proposes an online learning control system that uses the strategy of Model Predictive Control (MPC) in a model based locally weighted learning framework. The new approach, named Locally Weighted Learning Model Predictive Control (LWL-MPC), is proposed as a solution to learn to control robotic systems with nonlinear and time varying dynamics. This paper demonstrates the capability of LWL-MPC to perform online learning while controlling the joint trajectories of a low cost, three degree of freedom elastic joint robot. The learning performance is investigated in both an initial learning phase, and when the system dynamics change due to a heavy object added to the tool point. The experiment on the real elastic joint robot is presented and LWL-MPC is shown to successfully learn to control the system with and without the object. The results highlight the capability of the learning control system to accommodate the lack of mechanical consistency and linearity in a low cost robot arm.

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This study was a measure forward in cultivating the scientific basis for an approach to examine clinical procedure in Flapless dental implant surgery. The thesis is based on: the systematic review, retrospective study of flapless implants, and in vivo study on the osseo-integration in osteoporotic rats. Dr Doan investigated "clinical procedures used in dental implant treatment in posterior maxilla using flapless technique". The work has yielded significant contributions to the area of implant flapless surgery and its effects on osteoporotic patients having implants in the posterior maxilla.