Addressing issues in sparseness, ecological bias and formulation of the adjacency matrix in Bayesian spatio-temporal analysis of disease counts

The main objective of this PhD was to further develop Bayesian spatio-temporal models (specifically the Conditional Autoregressive (CAR) class of models), for the analysis of sparse disease outcomes such as birth defects. The motivation for the thesis arose from problems encountered when analyzing a large birth defect registry in New South Wales. The specific components and related research objectives of the thesis were developed from gaps in the literature on current formulations of the CAR model, and health service planning requirements. Data from a large probabilistically-linked database from 1990 to 2004, consisting of fields from two separate registries: the Birth Defect Registry (BDR) and Midwives Data Collection (MDC) were used in the analyses in this thesis. The main objective was split into smaller goals. The first goal was to determine how the specification of the neighbourhood weight matrix will affect the smoothing properties of the CAR model, and this is the focus of chapter 6. Secondly, I hoped to evaluate the usefulness of incorporating a zero-inflated Poisson (ZIP) component as well as a shared-component model in terms of modeling a sparse outcome, and this is carried out in chapter 7. The third goal was to identify optimal sampling and sample size schemes designed to select individual level data for a hybrid ecological spatial model, and this is done in chapter 8. Finally, I wanted to put together the earlier improvements to the CAR model, and along with demographic projections, provide forecasts for birth defects at the SLA level. Chapter 9 describes how this is done. For the first objective, I examined a series of neighbourhood weight matrices, and showed how smoothing the relative risk estimates according to similarity by an important covariate (i.e. maternal age) helped improve the model’s ability to recover the underlying risk, as compared to the traditional adjacency (specifically the Queen) method of applying weights. Next, to address the sparseness and excess zeros commonly encountered in the analysis of rare outcomes such as birth defects, I compared a few models, including an extension of the usual Poisson model to encompass excess zeros in the data. This was achieved via a mixture model, which also encompassed the shared component model to improve on the estimation of sparse counts through borrowing strength across a shared component (e.g. latent risk factor/s) with the referent outcome (caesarean section was used in this example). Using the Deviance Information Criteria (DIC), I showed how the proposed model performed better than the usual models, but only when both outcomes shared a strong spatial correlation. The next objective involved identifying the optimal sampling and sample size strategy for incorporating individual-level data with areal covariates in a hybrid study design. I performed extensive simulation studies, evaluating thirteen different sampling schemes along with variations in sample size. This was done in the context of an ecological regression model that incorporated spatial correlation in the outcomes, as well as accommodating both individual and areal measures of covariates. Using the Average Mean Squared Error (AMSE), I showed how a simple random sample of 20% of the SLAs, followed by selecting all cases in the SLAs chosen, along with an equal number of controls, provided the lowest AMSE. The final objective involved combining the improved spatio-temporal CAR model with population (i.e. women) forecasts, to provide 30-year annual estimates of birth defects at the Statistical Local Area (SLA) level in New South Wales, Australia. The projections were illustrated using sixteen different SLAs, representing the various areal measures of socio-economic status and remoteness. A sensitivity analysis of the assumptions used in the projection was also undertaken. By the end of the thesis, I will show how challenges in the spatial analysis of rare diseases such as birth defects can be addressed, by specifically formulating the neighbourhood weight matrix to smooth according to a key covariate (i.e. maternal age), incorporating a ZIP component to model excess zeros in outcomes and borrowing strength from a referent outcome (i.e. caesarean counts). An efficient strategy to sample individual-level data and sample size considerations for rare disease will also be presented. Finally, projections in birth defect categories at the SLA level will be made.

State of the arts and innovation : before and after the review of the national innovation system

This article examines the relationship between the arts and national innovation policy in Australia, pivoting around the Venturous Australia report released in September 2008 as part of the Review of the National Innovation System (RNIS). This came at a time of optimism that the arts sector would be included in Australia’s federal innovation policy. However, despite the report’s broad vision for innovation and specific commentary on the arts, the more ambitious hopes of arts sector advocates remained unfulfilled. This article examines the entwining discourses of creativity and innovation which emerged globally and in Australia prior to the RNIS, before analysing Venturous Australia in terms of the arts and the ongoing science-and-technology bias to innovation policy. It ends by considering why sector-led policy research and lobbying has to date proved unsuccessful and then suggests what public policy development is now needed.

Bias in the nonlinear filter generator output sequence

Nonlinear filter generators are common components used in the keystream generators for stream ciphers and more recently for authentication mechanisms. They consist of a Linear Feedback Shift Register (LFSR) and a nonlinear Boolean function to mask the linearity of the LFSR output. Properties of the output of a nonlinear filter are not well studied. Anderson noted that the m-tuple output of a nonlinear filter with consecutive taps to the filter function is unevenly distributed. Current designs use taps which are not consecutive. We examine m-tuple outputs from nonlinear filter generators constructed using various LFSRs and Boolean functions for both consecutive and uneven (full positive difference sets where possible) tap positions. The investigation reveals that in both cases, the m-tuple output is not uniform. However, consecutive tap positions result in a more biased distribution than uneven tap positions, with some m-tuples not occurring at all. These biased distributions indicate a potential flaw that could be exploited for cryptanalysis.

Bias in the nonlinear filter generator output sequence

Nonlinear filter generators are common components used in the keystream generators for stream ciphers and more recently for authentication mechanisms. They consist of a Linear Feedback Shift Register (LFSR) and a nonlinear Boolean function to mask the linearity of the LFSR output. Properties of the output of a nonlinear filter are not well studied. Anderson noted that the m-tuple output of a nonlinear filter with consecutive taps to the filter function is unevenly distributed. Current designs use taps which are not consecutive. We examine m-tuple outputs from nonlinear filter generators constructed using various LFSRs and Boolean functions for both consecutive and uneven (full positive difference sets where possible) tap positions. The investigation reveals that in both cases, the m-tuple output is not uniform. However, consecutive tap positions result in a more biased distribution than uneven tap positions, with some m-tuples not occurring at all. These biased distributions indicate a potential flaw that could be exploited for cryptanalysis

Reference bias : presentation of extreme health states prior to EQ-VAS improves health-related quality of life scores. A randomised crossover trial.

Background: Clinical practice and clinical research has made a concerted effort to move beyond the use of clinical indicators alone and embrace patient focused care through the use of patient reported outcomes such as healthrelated quality of life. However, unless patients give consistent consideration to the health states that give meaning to measurement scales used to evaluate these constructs, longitudinal comparison of these measures may be invalid. This study aimed to investigate whether patients give consideration to a standard health state rating scale (EQ-VAS) and whether consideration of good and poor health state descriptors immediately changes their selfreport. Methods: A randomised crossover trial was implemented amongst hospitalised older adults (n = 151). Patients were asked to consider descriptions of extremely good (Description-A) and poor (Description-B) health states. The EQ-VAS was administered as a self-report at baseline, after the first descriptors (A or B), then again after the remaining descriptors (B or A respectively). At baseline patients were also asked if they had considered either EQVAS anchors. Results: Overall 106/151 (70%) participants changed their self-evaluation by ≥5 points on the 100 point VAS, with a mean (SD) change of +4.5 (12) points (p < 0.001). A total of 74/151 (49%) participants did not consider the best health VAS anchor, of the 77 who did 59 (77%) thought the good health descriptors were more extreme (better) then they had previously considered. Similarly 85/151 (66%) participants did not consider the worst health anchor of the 66 who did 63 (95%) thought the poor health descriptors were more extreme (worse) then they had previously considered. Conclusions: Health state self-reports may not be well considered. An immediate significant shift in response can be elicited by exposure to a mere description of an extreme health state despite no actual change in underlying health state occurring. Caution should be exercised in research and clinical settings when interpreting subjective patient reported outcomes that are dependent on brief anchors for meaning. Trial Registration: Australian and New Zealand Clinical Trials Registry (#ACTRN12607000606482) http://www.anzctr. org.au

Response shift, recall bias and their effect on measuring change in health-related quality of life amongst older hospital patients

Background: Assessments of change in subjective patient reported outcomes such as health-related quality of life (HRQoL) are a key component of many clinical and research evaluations. However, conventional longitudinal evaluation of change may not agree with patient perceived change if patients' understanding of the subjective construct under evaluation changes over time (response shift) or if patients' have inaccurate recollection (recall bias). This study examined whether older adults' perception of change is in agreement with conventional longitudinal evaluation of change in their HRQoL over the duration of their hospital stay. It also investigated this level of agreement after adjusting patient perceived change for recall bias that patients may have experienced. Methods: A prospective longitudinal cohort design nested within a larger randomised controlled trial was implemented. 103 hospitalised older adults participated in this investigation at a tertiary hospital facility. The EQ-5D utility and Visual Analogue Scale (VAS) scores were used to evaluate HRQoL. Participants completed EQ-5D reports as soon as they were medically stable (within three days of admission) then again immediately prior to discharge. Three methods of change score calculation were used (conventional change, patient perceived change and patient perceived change adjusted for recall bias). Agreement was primarily investigated using intraclass correlation coefficients (ICC) and limits of agreement. Results: Overall 101 (98%) participants completed both admission and discharge assessments. The mean (SD) age was 73.3 (11.2). The median (IQR) length of stay was 38 (20-60) days. For agreement between conventional longitudinal change and patient perceived change: ICCs were 0.34 and 0.40 for EQ-5D utility and VAS respectively. For agreement between conventional longitudinal change and patient perceived change adjusted for recall bias: ICCs were 0.98 and 0.90 respectively. Discrepancy between conventional longitudinal change and patient perceived change was considered clinically meaningful for 84 (83.2%) of participants, after adjusting for recall bias this reduced to 8 (7.9%). Conclusions: Agreement between conventional change and patient perceived change was not strong. A large proportion of this disagreement could be attributed to recall bias. To overcome the invalidating effect of response shift (on conventional change) and recall bias (on patient perceived change) a method of adjusting patient perceived change for recall bias has been described.

European advanced driver training programs : reasons for optimism

Post license advanced driver training programs in the US and early programs in Europe have often failed to accomplish their stated objectives because, it is suspected, that drivers gain self perceived driving skills that exceed their true skills—leading to increased post training crashes. The consensus from the evaluation of countless advanced driver training programs is that these programs are a detriment to safety, especially for novice, young, male drivers. Some European countries including Sweden, Finland, Austria, Luxembourg, and Norway, have continued to refine these programs, with an entirely new training philosophy emerging around 1990. These ‘post-renewal’ programs have shown considerable promise, despite various data quality and availability concerns. These programs share in common a focus on teaching drivers about self assessment and anticipation of risk, as opposed to teaching drivers how to master driving at the limits of tire adhesion. The programs focus on factors such as self actualization and driving discipline, rather than low level mastery of skills. Drivers are meant to depart these renewed programs with a more realistic assessment of their driving abilities. These renewed programs require considerable specialized and costly infrastructure including dedicated driver training facilities with driving modules engineered specifically for advanced driver training and highly structured curricula. They are conspicuously missing from both the US road safety toolbox and academic literature. Given the considerable road safety concerns associated with US novice male drivers in particular, these programs warrant further attention. This paper reviews the predominant features and empirical evidence surrounding post licensing advanced driver training programs focused on novice drivers. A clear articulation of differences between the renewed and current US advanced driver training programs is provided. While the individual quantitative evaluations range from marginally to significantly effective in reducing novice driver crash risk, they have been criticized for evaluation deficiencies ranging from small sample sizes to confounding variables to lack of exposure metrics. Collectively, however, the programs sited in the paper suggest at least a marginally positive effect that needs to be validated with further studies. If additional well controlled studies can validate these programs, a pilot program in the US should be considered.

Exploring the impact of entrepreneur optimism on the new venture process

By integrating two theoretical foundations of entrepreneurship research, behaviour and process, this conceptual paper proposes a new model to examine the behaviour of the entrepreneur across the new venture development process. Existing macro level research on the new venture creation process recognises the entrepreneur as a central agent in the process yet generally avoids, at each stage of the process, an examination of the micro level psychological experiences of the individual entrepreneur. Similarly, behavioural research examining entrepreneur individual differences has failed to systematically explore the emotion and behaviour of the entrepreneur across the cycle of the new venture creation process. We propose a conceptual framework to integrate the new venture creation process of opportunity discovery, evaluation and exploitation, with the psychological capital (efficacy, hope, resilience and optimism) of the individual entrepreneur. Propositions for future research to facilitate deeper insight into the impact of entrepreneur behaviour on the new venture creation process and ultimately the success or failure of the new venture are provided.

PCR bias Toward the wild-type k-ras and p53 sequences: Implications for PCR detection of mutations and cancer diagnosis

PCR-based cancer diagnosis requires detection of rare mutations in k- ras, p53 or other genes. The assumption has been that mutant and wild-type sequences amplify with near equal efficiency, so that they are eventually present in proportions representative of the starting material. Work on factor IX suggests that this assumption is invalid for one case of near- sequence identity. To test the generality of this phenomenon and its relevance to cancer diagnosis, primers distant from point mutations in p53 and k-ras were used to amplify wild-type and mutant sequences from these genes. A substantial bias against PCR amplification of mutants was observed for two regions of the p53 gene and one region of k-ras. For k-ras and p53, bias was observed when the wild-type and mutant sequences were amplified separately or when mixed in equal proportions before PCR. Bias was present with proofreading and non-proofreading polymerase. Mutant and wild-type segments of the factor V, cystic fibrosis transmembrane conductance regulator and prothrombin genes were amplified and did not exhibit PCR bias. Therefore, the assumption of equal PCR efficiency for point mutant and wild-type sequences is invalid in several systems. Quantitative or diagnostic PCR will require validation for each locus, and enrichment strategies may be needed to optimize detection of mutants.

Reversed bias Pt/nanostructured ZnO Schottky diode with enhanced electric field for hydrogen sensing

In this paper, the effect of electric field enhancement on Pt/nanostructured ZnO Schottky diode based hydrogen sensors under reverse bias condition has been investigated. Current-voltage characteristics of these diodes have been studied at temperatures from 25 to 620 °C and their free carrier density concentration was estimated by exposing the sensors to hydrogen gas. The experimental results show a significantly lower breakdown voltage in reversed bias current-voltage characteristics than the conventional Schottky diodes and also greater lateral voltage shift in reverse bias operation than the forward bias. This can be ascribed to the increased localized electric fields emanating from the sharp edges and corners of the nanostructured morphologies. At 620 °C, voltage shifts of 114 and 325 mV for 0.06% and 1% hydrogen have been recorded from dynamic response under the reverse bias condition. © 2010 Elsevier B.V. All rights reserved.