Selection of working correlation structure and best model in GEE analyses of longitudinal data

The Generalized Estimating Equations (GEE) method is one of the most commonly used statistical methods for the analysis of longitudinal data in epidemiological studies. A working correlation structure for the repeated measures of the outcome variable of a subject needs to be specified by this method. However, statistical criteria for selecting the best correlation structure and the best subset of explanatory variables in GEE are only available recently because the GEE method is developed on the basis of quasi-likelihood theory. Maximum likelihood based model selection methods, such as the widely used Akaike Information Criterion (AIC), are not applicable to GEE directly. Pan (2001) proposed a selection method called QIC which can be used to select the best correlation structure and the best subset of explanatory variables. Based on the QIC method, we developed a computing program to calculate the QIC value for a range of different distributions, link functions and correlation structures. This program was written in Stata software. In this article, we introduce this program and demonstrate how to use it to select the most parsimonious model in GEE analyses of longitudinal data through several representative examples.

A preliminary analysis of the cost-effectiveness of the National Bowel Cancer Screening Program – demonstrating the potential value of comprehensive real world data

Background The complexity and cost of treating cancer patients is escalating rapidly and increasingly difficult decisions are being made regarding which interventions provide value for money. BioGrid Australia supports collection and analysis of comprehensive treatment and outcome data across multiple sites. Here we use preliminary data regarding the National Bowel Cancer Screening Program (NBCSP) and stage-specific treatment costs for colorectal cancer (CRC) to demonstrate the potential value of real world data for cost-effectiveness analyses (CEA).

Methods Data regarding the impact of NBCSP on stage at diagnosis was combined with stage-specific CRC treatment costs and existing literature. An incremental CEA was undertaken from a government healthcare perspective, comparing NBCSP to no-screening. The 2008 invited population (n=681,915) was modelled in both scenarios. Effectiveness was expressed as CRC-related life years saved (LYS). Costs and benefits were discounted at 3% per annum.

Results Over the lifetime and relative to no-screening, NBCSP was predicted to save 1,265 life-years, prevent 225 CRC cases and cost an additional $48.3 million, equivalent to a cost-effectiveness ratio of $38,217 per LYS. A scenario analysis assuming full participation improved this to $23,395.

Conclusions This preliminary CEA based largely on contemporary real world data suggests population-based FOBT screening for CRC is attractive. Planned ongoing data collection will enable repeated analyses over time, using the same methodology in the same patient populations, permitting an accurate analysis of the impact of new therapies and changing practice. Similar CEA using real world data related to other disease types and interventions appears desirable.

Adaptive data based neural network leader-follower control of multi-agent networks

In this paper, we propose a data based neural network leader-follower control for multi-agent networks where each agent is described by a class of high-order uncertain nonlinear systems with input perturbation. The control laws are developed using multiple-surface sliding control technique. In particular, novel set of sliding variables are proposed to guarantee leader-follower consensus on the sliding surfaces. Novel switching is proposed to overcome the unavailability of instantaneous control output from the neighbor. By utilizing RBF neural network and Fourier series to approximate the unknown functions, leader-follower consensus can be reached, under the condition that the dynamic equations of all agents are unknown. An O(n) data based algorithm is developed, using only the network’s measurable input/output data to generate the distributed virtual control laws. Simulation results demonstrate the effectiveness of the approach.

An iterative approach of protein function prediction

Background: Current approaches of predicting protein functions from a protein-protein interaction (PPI) dataset are based on an assumption that the available functions of the proteins (a.k.a. annotated proteins) will determine the functions of the proteins whose functions are unknown yet at the moment (a.k.a. un-annotated proteins). Therefore, the protein function prediction is a mono-directed and one-off procedure, i.e. from annotated proteins to un-annotated proteins. However, the interactions between proteins are mutual rather than static and mono-directed, although functions of some proteins are unknown for some reasons at present. That means when we use the similarity-based approach to predict functions of un-annotated proteins, the un-annotated proteins, once their functions are predicted, will affect the similarities between proteins, which in turn will affect the prediction results. In other words, the function prediction is a dynamic and mutual procedure. This dynamic feature of protein interactions, however, was not considered in the existing prediction algorithms.

Results: In this paper, we propose a new prediction approach that predicts protein functions iteratively. This iterative approach incorporates the dynamic and mutual features of PPI interactions, as well as the local and global semantic influence of protein functions, into the prediction. To guarantee predicting functions iteratively, we propose a new protein similarity from protein functions. We adapt new evaluation metrics to evaluate the prediction quality of our algorithm and other similar algorithms. Experiments on real PPI datasets were conducted to evaluate the effectiveness of the proposed approach in predicting unknown protein functions.

Conclusions: The iterative approach is more likely to reflect the real biological nature between proteins when predicting functions. A proper definition of protein similarity from protein functions is the key to predicting functions iteratively. The evaluation results demonstrated that in most cases, the iterative approach outperformed non-iterative ones with higher prediction quality in terms of prediction precision, recall and F-value.

Integrated modelling of cost-effective siting and operation of flow-control infrastructure for river ecosystem conservation

Wetland and floodplain ecosystems along many regulated rivers are highly stressed, primarily due to a lack of environmental flows of appropriate magnitude, frequency, duration, and timing to support ecological functions. In the absence of increased environmental flows, the ecological health of river ecosystems can be enhanced by the operation of existing and new flow-control infrastructure (weirs and regulators) to return more natural environmental flow regimes to specific areas. However, determining the optimal investment and operation strategies over time is a complex task due to several factors including the multiple environmental values attached to wetlands, spatial and temporal heterogeneity and dependencies, nonlinearity, and time-dependent decisions. This makes for a very large number of decision variables over a long planning horizon. The focus of this paper is the development of a nonlinear integer programming model that accommodates these complexities. The mathematical objective aims to return the natural flow regime of key components of river ecosystems in terms of flood timing, flood duration, and interflood period. We applied a 2-stage recursive heuristic using tabu search to solve the model and tested it on the entire South Australian River Murray floodplain. We conclude that modern meta-heuristics can be used to solve the very complex nonlinear problems with spatial and temporal dependencies typical of environmental flow allocation in regulated river ecosystems. The model has been used to inform the investment in, and operation of, flow-control infrastructure in the South Australian River Murray.

The value of sustainability in real estate : a review from a valuation perspective

Purpose – The purpose of this paper is to synthesise the plethora of research that has been conducted into the relationship between sustainability and market value in real estate, by critically analysing the research and the applicability of sustainability and value research in valuation practice.

Design/methodology/approach – The research on the relationship between sustainability and market value in real estate is examined from the perspective of its usefulness to the valuation profession in providing guidance, information and evidence to be used in valuation practice.

Findings – Existing research conducted into the relationship between sustainability and market value has not provided the valuation profession with evidence which would allow the incorporation of normative theories on the value of sustainability in valuation practice. This review highlights the lack of evidence, and the applicability of current research into sustainability and value to the valuation profession in providing guidance and information in valuing real estate incorporating sustainability.

Practical implications – This paper highlights the limited applicability of research to date in regard to the relationship between sustainability and market value for the valuation profession. The lack of historical evidence, data or information on the quantifiable effects on market value of this new trend (sustainability), leaves the valuation profession uncertain as to the relationship between sustainability and market value. There is a probable risk of valuers interpreting strategic research incorrectly, and making inappropriate adjustments or comparisons because of their lack of knowledge and limited sustainability assessment skills. Although there is an evolving body of knowledge, there is a need for extensive analysis of unbiased, evidence-based research in individual and broader markets to provide guidance, evidence and knowledge of the implications of sustainability in the valuation of real estate.

Originality/value – The examination of research investigating the relationship between sustainability and value from a valuation perspective provides an alternative insight into the applicability of current research in valuation practice. The increasing profile and role of sustainability in the real estate sector needs to be addressed in valuation practice; however, the variety of research to date needs to be interpreted by valuers in the correct context. This paper brings to light the applicability of sustainability and value research for the broader valuation profession, and the potential implications of misuse or misunderstanding of that research.

Real estate graduates’ employability skills : the perspective of human resource managers of surveying firms

Purpose – The purpose of this paper is to report further on research funded by the Centre for Education in the Built Environment (CEBE) into real estate programmes of study in UK universities (Poon and Hoxley). The aim of this paper is to identify human resource managers’ view on the employability skills of real estate graduates. It also compares the views on the employability skills of real estate graduates between human resource managers, a large sample of real estate employers and real estate course directors.

Design/methodology/approach – This paper presents the research findings of eight interviews with human resource managers who work in different types of surveying firms. The approach for collecting their view of the employability skills required by real estate graduates was through gathering their opinions on three charts. These charts compare what employers feel graduates require and what they feel graduates demonstrate in 31 knowledge areas, 20 skills and 21 attributes, alongside a list of additional competencies made by graduates and employers which was developed as part of an earlier study.

Findings – The human resource managers identified the key employability skills for real estate graduates as soft skills, in particular report writing skills, communication skills, presentation skills, client care and professional standards. The human resource managers of real estate consultancy firms also voiced their concern regarding graduates’ lack of commercial awareness, which echoed the same view from real estate employers and real estate course directors mentioned in the previous research (Poon, Hoxley and Fuchs). Therefore, it is necessary for universities to embed these soft skills, such as commercial awareness in the curriculum in order to enhance the employability of graduates.

Originality/value – This paper makes an original contribution to existing literature on the identification and discussion of employability skills for real estate graduates. It describes pioneering research focusing on the human resource managers’ perspective of the real estate graduate employability skills.

A critical evaluation and comparison of two formative measures of system quality using criterion variables

Evaluating the validity of formative variables has presented ongoing challenges for researchers. In this paper we use global criterion measures to compare and critically evaluate two alternative formative measures of System Quality. One model is based on the ISO-9126 software quality standard, and the other is based on a leading information systems research model. We find that despite both models having a strong provenance, many of the items appear to be non-significant in our study. We examine the implications of this by evaluating the quality of the criterion variables we used, and the performance of PLS when evaluating formative models with a large number of items. We find that our respondents had difficulty distinguishing between global criterion variables measuring different aspects of overall System Quality. Also, because formative indicators “compete with one another” in PLS, it may be difficult to develop a set of measures which are all significant for a complex formative construct with a broad scope and a large number of items. Overall, we suggest that there is cautious evidence that both sets of measures are valid and largely equivalent, although questions still remain about the measures, the use of criterion variables, and the use of PLS for this type of model evaluation.

Stochastic models of road geometry and wind condition for vehicle energy management and control

Modeling and simulation is commonly used to improve vehicle performance, to optimize vehicle system design, and to reduce vehicle development time. Vehicle performances can be affected by environmental conditions and driver behavior factors, which are often uncertain and immeasurable. To incorporate the role of environmental conditions in the modeling and simulation of vehicle systems, both real and artificial data are used. Often, real data are unavailable or inadequate for extensive investigations. Hence, it is important to be able to construct artificial environmental data whose characteristics resemble those of the real data for modeling and simulation purposes. However, to produce credible vehicle simulation results, the simulated environment must be realistic and validated using accepted practices. This paper proposes a stochastic model that is capable of creating artificial environmental factors such as road geometry and wind conditions. In addition, road geometric design principles are employed to modify the created road data, making it consistent with the real-road geometry. Two sets of real-road geometry and wind condition data are employed to propose probability models. To justify the distribution goodness of fit, Pearson's chi-square and correlation statistics have been used. Finally, the stochastic models of road geometry and wind conditions (SMRWs) are developed to produce realistic road and wind data. SMRW can be used to predict vehicle performance, energy management, and control strategies over multiple driving cycles and to assist in developing fuel-efficient vehicles.

Students’ views on the incorporation of commercial awareness in real estate education

Purpose – The purpose of this paper is to review how real estate students perceive and define commercial awareness, which is one of the most important employability skills. This paper also examines students’ perceptions about how their courses support and develop their commercial awareness. In addition, it compares students’ and academics’ views on commercial awareness and identifies whether there are any gaps.

Design/methodology/approach – This paper presents the research findings of a questionnaire survey and e-mail discussions with students who are currently studying Royal Institution of Chartered Surveyors (RICS)-accredited real estate courses in the UK. The questionnaire aimed to gather students’ views on the definitions and components of commercial awareness and identify what skills and attributes are required for its development. It also evaluates how commercial awareness has been embedded in the real estate courses. The aim of each discussion was to gain deeper insight on how components of commercial awareness are embedded in real estate courses, and 17 discussions were conducted. The contents of the e-mail discussions were analysed and similar themes were identified and coded. The frequency of the answer in the questionnaire and comments from interviewees is presented. The findings from students’ views have been compared to published research reporting UK RICS-accredited real estate course providers’ views on commercial awareness. In addition to descriptive statistics, Fisher’s exact test was used to identify the statistical significance between the academics’ and students’ views on commercial awareness.

Findings – The UK real estate students agreed that the most important definition of commercial awareness is a “person’s ability to understand the economics of business”. They agreed that “financial” component is the most important component of commercial awareness and it is the largest portion of their courses. The most important skill and attribute for commercial awareness development are “critical thinking” and “ability and willingness to update professional knowledge”, respectively. Although the descriptive analysis shows students and academics have different views on the definition and components of commercial awareness and its incorporation within real estate courses, the Fisher exact test shows that only a few elements are different enough to be statistically significant. This analysis shows that while students and academics have slightly different views on commercial awareness they are not very different.  Commercial awareness is an important employability skill, thus, it is still necessary for real estate academics to re-visit the curriculum and to ensure learning outcomes related to commercial awareness have been clearly explained and communicated to students. Furthermore, it is vital for students to obtain practical experience in order to fully develop their commercial awareness. 

Originality/value – This paper is a pioneer study focused on reviewing real estate students’ views on commercial awareness, including identifying its definition, components and evaluating the extent to which commercial awareness has been embedded in their courses. It also identifies the skills and attributes that students thought were required for the development of commercial awareness.  Furthermore, it discusses students’ preferred ways of enhancing their commercial awareness as part of the course they are studying. It is the first study identifying the statistical difference between students’ and academics’ views on commercial awareness. The understanding of students’ views on commercial awareness, their preferred delivery method and the divergence between students’ and academics’ views on commercial awareness can provide useful insights for course directors on the development and renewal of real estate course curriculum

Real-time ultrasound measures of lumbar erector spinae and multifidus: reliability and comparison to magnetic resonance imaging

In this work we examine the reliability and validity (in comparison to magnetic resonance imaging; MRI) of real-time ultrasound measures of lumbar erector spinae thickness. We also consider the between-day reliability of the lumbar multifidus muscle area as measured via ultrasound. 23 male subjects aged 21-45 years were measured three times over the course of nine days by one operator. The first (L1) through to the fifth (L5) lumbar vertebral levels were measured on the left and right sides. MRI was performed on the same day as first ultrasound scanning. For between-day intra-rater reliability, intra-class correlation co-efficients (ICCs), standard error of the measurement, minimal detectable difference and co-efficients of variation (CVs) were calculated along with their 95% confidence intervals and Bland-Altman analysis was performed. On Bland-Altman analysis, erector spinae thickness and multifidus area ultrasound measures 'agreed' with equivalent MR measures, though the correlation between MR and ultrasound measures was typically poor to moderate. For both ultrasound measures, the ICCs ranged from 'moderate' to 'excellent' at individual vertebral levels, although multifidus area (CV ranged from 8 to 15%) was less reliable than erector spinae thickness (CV ranged from 6 to 10%). 'Agreement' on Bland-Altmann analysis was present between days for all ultrasound measures. Averaging between sides and between vertebral levels improved reliability. Average erector spinae thickness showed a CV of 5.5% (ICC 0.77) and average multifidus area 6.2% (ICC 0.80).

Optimization Of Groundwater Remediation With New Efficient Parallel Algorithm For Global Optimization

Application of optimization algorithm to PDE modeling groundwater remediation can greatly reduce remediation cost. However, groundwater remediation analysis requires a computational expensive simulation, therefore, effective parallel optimization could potentially greatly reduce computational expense. The optimization algorithm used in this research is Parallel Stochastic radial basis function. This is designed for global optimization of computationally expensive functions with multiple local optima and it does not require derivatives. In each iteration of the algorithm, an RBF is updated based on all the evaluated points in order to approximate expensive function. Then the new RBF surface is used to generate the next set of points, which will be distributed to multiple processors for evaluation. The criteria of selection of next function evaluation points are estimated function value and distance from all the points known. Algorithms created for serial computing are not necessarily efficient in parallel so Parallel Stochastic RBF is different algorithm from its serial ancestor. The application for two Groundwater Superfund Remediation sites, Umatilla Chemical Depot, and Former Blaine Naval Ammunition Depot. In the study, the formulation adopted treats pumping rates as decision variables in order to remove plume of contaminated groundwater. Groundwater flow and contamination transport is simulated with MODFLOW-MT3DMS. For both problems, computation takes a large amount of CPU time, especially for Blaine problem, which requires nearly fifty minutes for a simulation for a single set of decision variables. Thus, efficient algorithm and powerful computing resource are essential in both cases. The results are discussed in terms of parallel computing metrics i.e. speedup and efficiency. We find that with use of up to 24 parallel processors, the results of the parallel Stochastic RBF algorithm are excellent with speed up efficiencies close to or exceeding 100%.

Allocation of authority in franchise chains

This article investigates the level of delegation in franchise chains, distinguishing the two most relevant franchising models: Business Format Franchising and Learning Network Franchising. The two models basically differ on the level of real authority (effective control over decisions) exercised by the franchisors. Differences in business features, such as the required standardization, monitoring costs and consumer sensitivity to variations in product attributes (consumer measurement costs), explain the adoption of the different models of franchising. These variables affect the trade-off between the risk of brand name loss and the gains in knowledge sharing and learning within the network. The higher the need for standardization, the higher is the risk of brand name loss, and, consequently, the more likely the franchisor will adopt an organizational design that confers more control over franchisees’ decisions, such as business format franchising. This paper presents two case studies with Brazilian food franchise chains that illustrate the main argument and suggest additional propositions. Moreover, an empirical analysis of 223 franchise chains provides additional support to the hypothesis of a negative the effect of required standardization on the level of delegation.

Câmbio real do Brasil : determinantes de longo prazo: evidências a partir de testes não paramétricos de cointegração e de tendência não linear comum

O trabalho procura investigar a existência de relação de cointegração entre a Taxa de Câmbio Real (CRER), Passivo Externo Líquido (PEL), Termos de Troca (TOT) e um fator de produtividade (BS), utilizando um teste não paramétrico proposto por Bierens (1997), aplicado a uma amostra de dados para EUA e Brasil que cobre o período de 1980 a 2010. Para os EUA, é encontrada evidência da influência das variáveis elencadas. No caso brasileiro verifica-se pouca relevância da variável BS, sendo as demais variáveis presentes no vetor de cointegração.

US real interest rates and default risk in emerging economies

This paper empirically investigates the impact of changes in US real interest rates on sovereign default risk in emerging economies using the method of identification through heteroskedasticity. Policy-induced increases in US interest rates starkly raise default risk in emerging market economies. However, the overall correlation between US real interest rates and the risk of default is negative, demonstrating that the effects of other variables dominate the anterior relationship