Links between unlicensed and unregistered driving (Data analysis). Report to Queensland Department of Transport and Main Roads

There is a current lack of understanding regarding the use of unregistered vehicles on public roads and road-related areas, and the links between the driving of unregistered vehicles and a range of dangerous driving behaviours. This report documents the findings of data analysis conducted to investigate the links between unlicensed driving and the driving of unregistered vehicles, and is an important initial undertaking into understanding these behaviours. This report examines de-identified data from two sources: crash data; and offence data. The data was extracted from the Queensland Department of Transport and Main Roads (TMR) databases and covered the period from 2003 to 2008.

A principled experimental design approach to Big Data analysis

Big Datasets are endemic, but they are often notoriously difficult to analyse because of their size, heterogeneity, history and quality. The purpose of this paper is to open a discourse on the use of modern experimental design methods to analyse Big Data in order to answer particular questions of interest. By appealing to a range of examples, it is suggested that this perspective on Big Data modelling and analysis has wide generality and advantageous inferential and computational properties. In particular, the principled experimental design approach is shown to provide a flexible framework for analysis that, for certain classes of objectives and utility functions, delivers near equivalent answers compared with analyses of the full dataset under a controlled error rate. It can also provide a formalised method for iterative parameter estimation, model checking, identification of data gaps and evaluation of data quality. Finally, it has the potential to add value to other Big Data sampling algorithms, in particular divide-and-conquer strategies, by determining efficient sub-samples.

Intra-cluster correlation structure in longitudinal data analysis: Selection criteria and misspecification tests

Selection criteria and misspecification tests for the intra-cluster correlation structure (ICS) in longitudinal data analysis are considered. In particular, the asymptotical distribution of the correlation information criterion (CIC) is derived and a new method for selecting a working ICS is proposed by standardizing the selection criterion as the p-value. The CIC test is found to be powerful in detecting misspecification of the working ICS structures, while with respect to the working ICS selection, the standardized CIC test is also shown to have satisfactory performance. Some simulation studies and applications to two real longitudinal datasets are made to illustrate how these criteria and tests might be useful.

Modeling strategies in longitudinal data analysis: Covariate, variance function and correlation structure selection

A modeling paradigm is proposed for covariate, variance and working correlation structure selection for longitudinal data analysis. Appropriate selection of covariates is pertinent to correct variance modeling and selecting the appropriate covariates and variance function is vital to correlation structure selection. This leads to a stepwise model selection procedure that deploys a combination of different model selection criteria. Although these criteria find a common theoretical root based on approximating the Kullback-Leibler distance, they are designed to address different aspects of model selection and have different merits and limitations. For example, the extended quasi-likelihood information criterion (EQIC) with a covariance penalty performs well for covariate selection even when the working variance function is misspecified, but EQIC contains little information on correlation structures. The proposed model selection strategies are outlined and a Monte Carlo assessment of their finite sample properties is reported. Two longitudinal studies are used for illustration.

Efficient parameter estimation in longitudinal data analysis using a hybrid GEE method

The method of generalized estimating equations (GEEs) provides consistent estimates of the regression parameters in a marginal regression model for longitudinal data, even when the working correlation model is misspecified (Liang and Zeger, 1986). However, the efficiency of a GEE estimate can be seriously affected by the choice of the working correlation model. This study addresses this problem by proposing a hybrid method that combines multiple GEEs based on different working correlation models, using the empirical likelihood method (Qin and Lawless, 1994). Analyses show that this hybrid method is more efficient than a GEE using a misspecified working correlation model. Furthermore, if one of the working correlation structures correctly models the within-subject correlations, then this hybrid method provides the most efficient parameter estimates. In simulations, the hybrid method's finite-sample performance is superior to a GEE under any of the commonly used working correlation models and is almost fully efficient in all scenarios studied. The hybrid method is illustrated using data from a longitudinal study of the respiratory infection rates in 275 Indonesian children.

Weighted rank regression for clustered data analysis

We consider ranked-based regression models for clustered data analysis. A weighted Wilcoxon rank method is proposed to take account of within-cluster correlations and varying cluster sizes. The asymptotic normality of the resulting estimators is established. A method to estimate covariance of the estimators is also given, which can bypass estimation of the density function. Simulation studies are carried out to compare different estimators for a number of scenarios on the correlation structure, presence/absence of outliers and different correlation values. The proposed methods appear to perform well, in particular, the one incorporating the correlation in the weighting achieves the highest efficiency and robustness against misspecification of correlation structure and outliers. A real example is provided for illustration.

Robust estimating functions and bias correction for longitudinal data analysis

Robust methods are useful in making reliable statistical inferences when there are small deviations from the model assumptions. The widely used method of the generalized estimating equations can be "robustified" by replacing the standardized residuals with the M-residuals. If the Pearson residuals are assumed to be unbiased from zero, parameter estimators from the robust approach are asymptotically biased when error distributions are not symmetric. We propose a distribution-free method for correcting this bias. Our extensive numerical studies show that the proposed method can reduce the bias substantially. Examples are given for illustration.

Estimating equations for removal data analysis

We consider the problem of estimating a population size from successive catches taken during a removal experiment and propose two estimating functions approaches, the traditional quasi-likelihood (TQL) approach for dependent observations and the conditional quasi-likelihood (CQL) approach using the conditional mean and conditional variance of the catch given previous catches. Asymptotic covariance of the estimates and the relationship between the two methods are derived. Simulation results and application to the catch data from smallmouth bass show that the proposed estimating functions perform better than other existing methods, especially in the presence of overdispersion.

Preparing library staff for research support services at QUT

INTRODUCTION: Queensland University of Technology (QUT) Library is partnering with High Performance Computing (HPC) services and the Division of Research and Commercialisation to develop and deliver a range of integrated research support services and systems designed to enhance the research capabilities of the University. Existing and developing research support services include - support for publishing strategies including open access, bibliographic citation and ranking services, research data management, use of online collaboration tools, online survey tools, quantitative and qualitative data analysis, content management and storage solutions. In order to deliver timely and effective research referral and support services, it is imperative that library staff maintain their awareness of, and develop expertise in new eResearch methods and technologies. ---------- METHODS: In 2009/10 QUT Library initiated an online survey for support staff and researchers and a series of focus groups for researchers aimed at gaining a better understanding of current and future eresearch practices and skills. These would better inform the development of a research skills training program and the development of new research support services. The Library and HPC also implemented a program of seminars and workshops designed to introduce key library staff to a broad range of eresearch concepts and technologies. Feedback was obtained after each training session. A number of new services were implemented throughout 2009 and 2010. ---------- RESULTS: Key findings of the survey and focus groups are related to the development of the staff development program. Feedback from program attendees is provided and evaluated. The staff development program is assessed in terms of its success to support the implementation of new research support services. --------- CONCLUSIONS QUT Library has embarked on an ambitious awareness and skills development program to assist Library staff transition a period of rapid change and broadening scope for the Library. Successes and challenges of the program are discussed. A number of recommendations are made in retrospect and also looking forward to the future training needs of Library staff to support the University’s future research goals.

Conceptualising use for information systems (IS) success

This thesis conceptualises Use for IS (Information Systems) success. While Use in this study describes the extent to which an IS is incorporated into the user’s processes or tasks, success of an IS is the measure of the degree to which the person using the system is better off. For IS success, the conceptualisation of Use offers new perspectives on describing and measuring Use. We test the philosophies of the conceptualisation using empirical evidence in an Enterprise Systems (ES) context. Results from the empirical analysis contribute insights to the existing body of knowledge on the role of Use and demonstrate Use as an important factor and measure of IS success. System Use is a central theme in IS research. For instance, Use is regarded as an important dimension of IS success. Despite its recognition, the Use dimension of IS success reportedly suffers from an all too simplistic definition, misconception, poor specification of its complex nature, and an inadequacy of measurement approaches (Bokhari 2005; DeLone and McLean 2003; Zigurs 1993). Given the above, Burton-Jones and Straub (2006) urge scholars to revisit the concept of system Use, consider a stronger theoretical treatment, and submit the construct to further validation in its intended nomological net. On those considerations, this study re-conceptualises Use for IS success. The new conceptualisation adopts a work-process system-centric lens and draws upon the characteristics of modern system types, key user groups and their information needs, and the incorporation of IS in work processes. With these characteristics, the definition of Use and how it may be measured is systematically established. Use is conceptualised as a second-order measurement construct determined by three sub-dimensions: attitude of its users, depth, and amount of Use. The construct is positioned in a modified IS success research model, in an attempt to demonstrate its central role in determining IS success in an ES setting. A two-stage mixed-methods research design—incorporating a sequential explanatory strategy—was adopted to collect empirical data and to test the research model. The first empirical investigation involved an experiment and a survey of ES end users at a leading tertiary education institute in Australia. The second, a qualitative investigation, involved a series of interviews with real-world operational managers in large Indian private-sector companies to canvass their day-to-day experiences with ES. The research strategy adopted has a stronger quantitative leaning. The survey analysis results demonstrate the aptness of Use as an antecedent and a consequence of IS success, and furthermore, as a mediator between the quality of IS and the impacts of IS on individuals. Qualitative data analysis on the other hand, is used to derive a framework for classifying the diversity of ES Use behaviour. The qualitative results establish that workers Use IS in their context to orientate, negotiate, or innovate. The implications are twofold. For research, this study contributes to cumulative IS success knowledge an approach for defining, contextualising, measuring, and validating Use. For practice, research findings not only provide insights for educators when incorporating ES for higher education, but also demonstrate how operational managers incorporate ES into their work practices. Research findings leave the way open for future, larger-scale research into how industry practitioners interact with an ES to complete their work in varied organisational environments.

Understanding the phenomenon of IS success in China through the lens of the IS-Impact model

This study is conducted within the IS-Impact Research Track at Queensland University of Technology (QUT). The goal of the IS-Impact Track is, “to develop the most widely employed model for benchmarking information systems in organizations for the joint benefit of both research and practice” (Gable et al, 2006). IS-Impact is defined as “a measure at a point in time, of the stream of net benefits from the IS, to date and anticipated, as perceived by all key-user-groups” (Gable Sedera and Chan, 2008). Track efforts have yielded the bicameral IS-Impact measurement model; the “impact” half includes Organizational-Impact and Individual-Impact dimensions; the “quality” half includes System-Quality and Information-Quality dimensions. The IS-Impact model, by design, is intended to be robust, simple and generalizable, to yield results that are comparable across time, stakeholders, different systems and system contexts. The model and measurement approach employ perceptual measures and an instrument that is relevant to key stakeholder groups, thereby enabling the combination or comparison of stakeholder perspectives. Such a validated and widely accepted IS-Impact measurement model has both academic and practical value. It facilitates systematic operationalization of a main dependent variable in research (IS-Impact), which can also serve as an important independent variable. For IS management practice it provides a means to benchmark and track the performance of information systems in use. The objective of this study is to develop a Mandarin version IS-Impact model, encompassing a list of China-specific IS-Impact measures, aiding in a better understanding of the IS-Impact phenomenon in a Chinese organizational context. The IS-Impact model provides a much needed theoretical guidance for this investigation of ES and ES impacts in a Chinese context. The appropriateness and soundness of employing the IS-Impact model as a theoretical foundation are evident: the model originated from a sound theory of IS Success (1992), developed through rigorous validation, and also derived in the context of Enterprise Systems. Based on the IS-Impact model, this study investigates a number of research questions (RQs). Firstly, the research investigated what essential impacts have been derived from ES by Chinese users and organizations [RQ1]. Secondly, we investigate which salient quality features of ES are perceived by Chinese users [RQ2]. Thirdly, we seek to answer whether the quality and impacts measures are sufficient to assess ES-success in general [RQ3]. Lastly, the study attempts to address whether the IS-Impact measurement model is appropriate for Chinese organizations in terms of evaluating their ES [RQ4]. An open-ended, qualitative identification survey was employed in the study. A large body of short text data was gathered from 144 Chinese users and 633 valid IS-Impact statements were generated from the data set. A generally inductive approach was applied in the qualitative data analysis. Rigorous qualitative data coding resulted in 50 first-order categories with 6 second-order categories that were grounded from the context of Chinese organization. The six second-order categories are: 1) System Quality; 2) Information Quality; 3) Individual Impacts;4) Organizational Impacts; 5) User Quality and 6) IS Support Quality. The final research finding of the study is the contextualized Mandarin version IS-Impact measurement model that includes 38 measures organized into 4 dimensions: System Quality, information Quality, Individual Impacts and Organizational Impacts. The study also proposed two conceptual models to harmonize the IS-Impact model and the two emergent constructs – User Quality and IS Support Quality by drawing on previous IS effectiveness literatures and the Work System theory proposed by Alter (1999) respectively. The study is significant as it is the first effort that empirically and comprehensively investigates IS-Impact in China. Specifically, the research contributions can be classified into theoretical contributions and practical contributions. From the theoretical perspective, through qualitative evidence, the study test and consolidate IS-Impact measurement model in terms of the quality of robustness, completeness and generalizability. The unconventional research design exhibits creativity of the study. The theoretical model does not work as a top-down a priori seeking for evidence demonstrating its credibility; rather, the study allows a competitive model to emerge from the bottom-up and open-coding analysis. Besides, the study is an example extending and localizing pre-existing theory developed in Western context when the theory is introduced to a different context. On the other hand, from the practical perspective, It is first time to introduce prominent research findings in field of IS Success to Chinese academia and practitioner. This study provides a guideline for Chinese organizations to assess their Enterprise System, and leveraging IT investment in the future. As a research effort in ITPS track, this study contributes the research team with an alternative operationalization of the dependent variable. The future research can take on the contextualized Mandarin version IS-Impact framework as a theoretical a priori model, further quantitative and empirical testing its validity.

Physical activity in the lives of those living with lymphoedema following cancer treatment

Background Despite recent evidence demonstrating that exercise neither increases risk of nor exacerbates lymphoedema, lymphoedema prevention and management advice cautions against ‘repetitive use’ or ‘overuse’ of the affected arm. It is plausible that this advice creates a barrier to participation in exercise and, more generally, physical activity (any daily activity [PA]). This study explored the relationship between lymphoedema and PA among people following cancer treatment. Methods Social constructionist grounded theory guided study design, development of interview questions and the qualitative data analysis approach undertaken. Data were collected via focus groups and telephone interviews. Results Five focus groups (n=16 participants) and 13 telephone interviews were completed. Participants (women n=26, men n=3) were aged 39-80 years and were experiencing mild to severe lymphoedema following treatment for a variety of cancers. Participants varied in how they defined PA. Its perceived importance was mostly associated with the ability to partake in daily activities, with only some participants highlighting its importance for lymphoedema management or more general health benefits. Most participants’ PA decreased after diagnosis, a consequence of confusion around appropriate PA and fear that PA could worsen lymphoedema symptoms. Conclusions Lymphoedema guidelines need to be more clear and specific when discussing the role of PA and exercise in the prevention and management of lymphoedema. It may be more appropriate to discuss ways to optimize safety when engaging in specific tasks rather than to highlight the need for avoidance of participating in certain activities.

How do older adults respond to Active Australia physical activity questions? Lessons from cognitive interviews

The aim of this study was to examine older adults’ understanding and interpretation of a validated questionnaire for physical activity surveillance, the Active Australia Survey (AAS). To address this aim, cognitive interviewing techniques were used during face-to-face semi-structured interviews with 44 adults aged 65-89 years. Qualitative data analysis revealed that participants were confused with questionnaire phrasing, misunderstood the scope of activities to include in answers, and misunderstood the time frame of activities to report. They also struggled to accurately estimate the frequency and duration of their activities. Our findings suggest that AAS questions may be interpreted differently by older adults than intended by survey developers. Findings also suggest that older adults use a range of methods for calculating PA frequency and duration. The issues revealed in this study may be useful for adapting AAS for use in older community-dwelling adults.

Analysing governance categories used on project alliances in the construction industry

In Australia, collaborative contracts, and in particular, project alliances, have been increasingly used to govern infrastructure projects. These contracts use formal and informal governance mechanisms to manage the delivery of infrastructure projects. Formal mechanisms such as financial risk sharing are specified in the contract, while informal mechanisms such as integrated teams are not. Given that the literature contains a multiplicity of often untestable definitions, this paper reports on a review of the literature to operationalize the concepts of formal and informal governance. This work is the first phase of a study that will examine the optimal balance of formal and informal governance structures. Desk-top review of leading journals in the areas of construction management and business management, as well as recent government documents and industry guidelines, was undertaken to to conceptualise and operationalize formal and informal governance mechanisms. The study primarily draws on transaction-cost economics (e.g. Williamson 1979; Williamson 1991), relational contract theory (Feinman 2000; Macneil 2000) and social psychology theory (e.g. Gulati 1995). Content analysis of the literature was undertaken to identify key governance mechanisms. Content analysis is a commonly used methodology in the social sciences area. It provides rich data through the systematic and objective review of literature (Krippendorff 2004). NVivo 9, a qualitative data analysis software package, was used to assist in this process. A previous study by the authors identified that formal governance mechanisms can be classified into seven measurable categories: (1) negotiated cost, (2) competitive cost, (3) commercial framework, (4) risk and reward sharing, (5) qualitative performance, (6) collaborative multi-party agreement, and (7) early contractor involvement. Similarly, informal governance mechanisms can be classified into four measureable categories: (1) leadership structure, (2) integrated team, (3) team workshops, and (4) joint management system. This paper explores and further defines the key operational characteristics of each mechanism category, highlighting its impact on value for money in alliance project delivery. The paper’s contribution is that it provides the basis for future research to compare the impact of a range of individual mechanisms within each category, as a means of improving the performance of construction projects.

Using NVivo as a research management tool : a case narrative

This paper presents an illustrative demonstration of the qualitative data analysis tool NVivo (version 2.0), as employed across a multi-method research design as a comprehensive tool in support of overall research management. The paper will be of interest to (a) novice researchers, as a reference in their research design efforts; (b) academics, involved in research training, where this narrative can be used as a rich teaching case and; potentially to (c) vendors, of similar software tools, who may identify potential new tool applications and valuable tool enhancements.