Regulating bereavement : inquests, family pressure and the gate keeping of suicide statistics

This study of English Coronial practice raises a number of questions, not only regarding state investigations of suicide, but also of the role of the Coroner itself. Following observations at over 20 inquests into possible suicides, and in-depth interviews with six Coroners, three main issue emerged: first, there exists considerable slippage between different Coroners over which deaths are likely to be classified as suicide; second, the high standard of proof required, and immense pressure faced by Coroners from family members at inquest to reach any verdict other than suicide, can significantly depress likely suicide rates; and finally, Coroners feel no professional obligation, either individually or collectively, to contribute to the production of consistent and useful social data regarding suicide—arguably rendering comparative suicide statistics relatively worthless. These issues lead, ultimately, to a more important question about the role we expect Coroners to play within social governance, and within an effective, contemporary democracy.

Sleepy driving and pulling over for a rest : investigating individual factors that contribute to these driving behaviours

Driver sleepiness is a substantial crash risk factor and as such, is a major contributor to crash statistics. A number of individual factors (i.e., psychological factors) have been suggested to influence driving while sleepy. However, few studies have examined the influence of these individual factors for sleepy driving in combination. The current study sought to examine how various demographic factors, attitudes, perceived legitimacy, personality constructs, and risk taking variables were associated with self-reported likelihood of driving sleepy and pulling over and resting when sleepy. The results show that being a younger driver, having positive attitudes towards driving sleepy, and high levels of emotional stability were related to self-reported likelihood of driving sleepy. Whereas, being an older driver and having negative attitudes towards driving sleepy were associated with self-reported likelihood of pulling over and resting when sleepy. Overall, the obtained results suggest that the age and attitudes of the driver have greater influence than personality traits or risk taking factors. Campaigns focused on changing attitudes to reflect the dangerousness of sleepy driving could be important for road safety outcomes.

Projecting the trend in the Canadian gender wage gap 2001-2031: Will an increase in female education acquisition and commitment be enough?

The paper projects the gender wage gap for 25-64 year-olds in Canada over the period 2001-2031. The empirical analysis uses the Survey of Labour and Income Dynamics together with Statistics Canada demographic projections. The methodology combines the population projections with assumptions relating to the evolution of educational attainment in order to first project the future distribution of human capital skills and, based on these projections, the future size of the gender wage gap. The projections suggest continued gender wage convergence produced by changing skills characteristics. However, a substantial pay gap will remain in 2031.

The gender wage gap in Australia - The path of future convergence

The paper attempts to project the future trend of the gender wage gap in Australia up to 2031. The empirical analysis utilises the Income Distribution Survey (1996) together with Australian Bureau of Statistics (ABS) demographic projections. The methodology combines the ABS projections with assumptions relating to the evolution of educational attainment in order to project the future distribution of human capital skills and consequently the future size of the gender wage gap. The analysis suggests that female relative pay will continue to rise up to 2031. However, gender wage convergence will be relatively slow, with a substantial gap remaining in 2031.

Projections of the future path of the gender wage gap in Great Britain

Purpose – The paper attempts to project the future trend of the gender wage gap in Great Britain up to 2031. Design/methodology/approach – The empirical analysis utilises the British Household Panel Study Wave F together with Office for National Statistics (ONS) demographic projections. The methodology combines the ONS projections with assumptions relating to the evolution of educational attainment in order to project the future distribution of human capital skills and consequently the future size of the gender wage gap. Findings – The analysis suggests that gender wage convergence will be slow, with little female progress by 2031 unless there is a large rise in returns to female experience. Originality/value – The paper has projected the pattern of male and female skill acquisition together with the associated trend in wages up to 2031.

Evaluating the use of online synchronous communication to enhance learning in statistics

According to social constructivists, learners are active participants in constructing new knowledge in a social process where they interact with others. In these social settings teachers or more knowledgeable peers provide support. This research study investigated the contribution that an online synchronous tutorial makes to support teaching and learning of undergraduate introductory statistics offered by an Australian regional university at a distance. The introductory statistics course which served as a research setting in this study was a requirement of a variety of programs at the University, including psychology, business and science. Often students in these programs perceive this course to be difficult and irrelevant to their programs of study. Negative attitudes and associated anxiety mean that students often struggle with the content. While asynchronous discussion forums have been shown to provide a level of interaction and support, it was anticipated that online synchronous tutorials would offer immediate feedback to move students forward through ―stuck places.‖ At the beginning of the semester the researcher offered distance students in this course the opportunity to participate in a weekly online synchronous tutorial which was an addition to the usual support offered by the teaching team. This tutorial was restricted to 12 volunteers to allow sufficient interaction to occur for each of the participants. The researcher, as participant-observer, conducted the weekly tutorials using the University's interactive online learning platform, Wimba Classroom, whereby participants interacted using audio, text chat and a virtual whiteboard. Prior to the start of semester, participants were surveyed about their previous mathematical experiences, their perceptions of the introductory statistics course and why they wanted to participate in the online tutorial. During the semester, they were regularly asked pertinent research questions related to their personal outcomes from the tutorial sessions. These sessions were recorded using screen capture software and the participants were interviewed about their experiences at the end of the semester. Analysis of these data indicated that the perceived value of online synchronous tutorial lies in the interaction with fellow students and a content expert and with the immediacy of feedback given. The collaborative learning environment offered the support required to maintain motivation, enhance confidence and develop problemsolving skills in these distance students of introductory statistics. Based on these findings a model of online synchronous learning is proposed.

Determinants of the frequency of contact lens wear

Objectives To characterize and discover the determinants of the frequency of wear (FOW) of contact lenses. Methods Survey forms were sent to contact lens fitters in up to 40 countries between January and March every year for 5 consecutive years (2007–2011). Practitioners were asked to record data relating to the first 10 contact lens fits or refits performed after receiving the survey form. Only data for daily wear lens fits were analyzed. Results Data were collected in relation to 74,510 and 9,014 soft and rigid lens fits, respectively. Overall, FOW was 5.9±1.7 days per week (DPW). When considering the proportion of lenses worn between one to seven DPW, the distribution for rigid lenses is skewed toward full-time wear (7 DPW), whereas the distribution for soft daily disposable lenses is perhaps bimodal, with large and small peaks at seven and two DPW, respectively. There is a significant variation in FOW among nations (P<0.0001), ranging from 6.8±1.0 DPW in Greece to 5.1±2.5 DPW in Kuwait. For soft lenses, FOW increases with decreasing age. Females (6.0±1.6 DPW) wear lenses more frequently than males (5.8±1.7 DPW) (P=0.0002). FOW is greater among those wearing presbyopic corrections (6.1±1.4 DPW) compared with spherical (5.9±1.7 DPW) and toric (5.9±1.6 DPW) designs (P<0.0001). FOW with hydrogel peroxide systems (6.4±1.1 DPW) was greater than that with multipurpose systems (6.2±1.3 DPW) (P<0.0001). Conclusions Numerous demographic and contact lens–related factors impact FOW. There may be a future trend toward a lower FOW associated with the increasing popularity of daily disposable lenses.

Statistical modelling of district-level residential electricity use in NSW, Australia

Electricity network investment and asset management require accurate estimation of future demand in energy consumption within specified service areas. For this purpose, simple models are typically developed to predict future trends in electricity consumption using various methods and assumptions. This paper presents a statistical model to predict electricity consumption in the residential sector at the Census Collection District (CCD) level over the state of New South Wales, Australia, based on spatial building and household characteristics. Residential household demographic and building data from the Australian Bureau of Statistics (ABS) and actual electricity consumption data from electricity companies are merged for 74 % of the 12,000 CCDs in the state. Eighty percent of the merged dataset is randomly set aside to establish the model using regression analysis, and the remaining 20 % is used to independently test the accuracy of model prediction against actual consumption. In 90 % of the cases, the predicted consumption is shown to be within 5 kWh per dwelling per day from actual values, with an overall state accuracy of -1.15 %. Given a future scenario with a shift in climate zone and a growth in population, the model is used to identify the geographical or service areas that are most likely to have increased electricity consumption. Such geographical representation can be of great benefit when assessing alternatives to the centralised generation of energy; having such a model gives a quantifiable method to selecting the 'most' appropriate system when a review or upgrade of the network infrastructure is required.

Learning detectors quickly with stationary statistics

Computer vision is increasingly becoming interested in the rapid estimation of object detectors. The canonical strategy of using Hard Negative Mining to train a Support Vector Machine is slow, since the large negative set must be traversed at least once per detector. Recent work has demonstrated that, with an assumption of signal stationarity, Linear Discriminant Analysis is able to learn comparable detectors without ever revisiting the negative set. Even with this insight, the time to learn a detector can still be on the order of minutes. Correlation filters, on the other hand, can produce a detector in under a second. However, this involves the unnatural assumption that the statistics are periodic, and requires the negative set to be re-sampled per detector size. These two methods differ chie y in the structure which they impose on the co- variance matrix of all examples. This paper is a comparative study which develops techniques (i) to assume periodic statistics without needing to revisit the negative set and (ii) to accelerate the estimation of detectors with aperiodic statistics. It is experimentally verified that periodicity is detrimental.

Cell image classification using histograms, higher order statistics and adaboost

A cell classification algorithm that uses first, second and third order statistics of pixel intensity distributions over pre-defined regions is implemented and evaluated. A cell image is segmented into 6 regions extending from a boundary layer to an inner circle. First, second and third order statistical features are extracted from histograms of pixel intensities in these regions. Third order statistical features used are one-dimensional bispectral invariants. 108 features were considered as candidates for Adaboost based fusion. The best 10 stage fused classifier was selected for each class and a decision tree constructed for the 6-class problem. The classifier is robust, accurate and fast by design.

Discussion of : constructing summary statistics for approximate Bayesian computation: semi-automatic approximate Bayesian computation

This is a discussion of the journal article: "Construcing summary statistics for approximate Bayesian computation: semi-automatic approximate Bayesian computation". The article and discussion have appeared in the Journal of the Royal Statistical Society: Series B (Statistical Methodology).

Ageing in suburbia : designing for demographic change in Australia and New Zealand

In the next half-century, Australia's population of people aged over 65 is set to almost double. As a consequence, there is an urgent need in both Australia and New Zealand, where older people value their independence, for housing that fully supports them in their own suburban homes. With only a handful of models in place, Mark Taylor, Professor of Architecture at the University of Newcastle, Australia, and Laurie Buys, a Professor in the School of Design at Queensland University of Technology in Brisbane, have tracked down some promising precedents for suburban living in adapted homes and within community-based shared housing.

Socio-demographic characteristics, modifiable lifestyle factors, and health as predictors of mental health in midlife and older Australian women: a multilevel investigation

Background Poor mental health is a significant cause of morbidity and mortality, yet debate continues about factors most likely to predict poor mental health outcomes. Objective This cohort study examines the influence of modifiable lifestyle factors, menopausal symptoms, and physical health on the mental health of midlife and older Australian women. Methods: Random sampling was used to recruit women aged 40-55, from rural and urban areas of Queensland, Australia. Overall, 340 women completed mailed surveys on socio-demographic characteristics, midlife symptoms (Greene Climacteric Scale©), modifiable lifestyle factors, and mental health (SF-12©) in 2001, 2004 and 2011. Hierarchical repeated-measure models were used to explore the correlates of poor mental health over time. Results The mean age [SD] at baseline was 55 [2.7] years, most were married (73%, n=248) and 18% were pre-menopausal. The model suggested that variance in mental health widened and showed a non-linear increase with age. Decrements in mental health were associated with an increase in midlife symptoms (Greene psychological scale, P <0.01; Greene somatic scale, P <0.05), time (P <0.01), poor physical health (P <0.01) and individual variance (P <0.01). Socio-demographics and lifestyle factors had little influence on mental health over time. Conclusion Findings suggest that while women’s mental health may decline during midlife, the effect is temporary; in older women, physical health and individual factors seem to be increasingly significant. This research highlights the importance of active health promotion as a means of enhancing both physical and mental health in midlife women.

What aspects of demographic, personality, attitudes, and perceptions of law enforcement influence self-reported likelihood of drink driving?

The aim of the current study was to examine the associations between a number of individual factors (demographic factors (age and gender), personality factors, risk-taking propensity, attitudes towards drink driving, and perceived legitimacy of drink driving enforcement) and how they influence the self-reported likelihood of drink driving. The second aim of this study was to examine the potential of attitudes mediating the relationship between risk-taking and self-reported likelihood of drink driving. In total, 293 Queensland drivers volunteered to participate in an online survey that assessed their self-reported likelihood to drink drive in the next month, demographics, traffic-related demographics, personality factors, risk-taking propensity, attitudes towards drink driving, and perceived legitimacy of drink driving enforcement. An ordered logistic regression analysis was utilised to evaluate the first aim of the study; at the first step the demographic variables were entered; at step two the personality and risk-taking were entered; at the third step, the attitudes and perceptions of legitimacy variables were entered. Being a younger driver and having a high risk-taking propensity were related to self-reported likelihood of drink driving. However, when the attitudes variable was entered, these individual factors were no longer significant; with attitudes being the most important predictor of self-reported drink driving likelihood. A significant mediation model was found with the second aim of the study, such that attitudes mediated the relationship between risk-taking and self-reported likelihood of drink driving. Considerable effort and resources are utilised by traffic authorities to reducing drink driving on the Australian road network. Notwithstanding these efforts, some participants still had some positive attitudes towards drink driving and reported that they were likely to drink drive in the future. These findings suggest that more work is needed to address attitudes regarding the dangerousness of drink driving.

Bluetooth vehicle trajectory by fusing Bluetooth and loops : motorway travel time statistics

Loop detectors are widely used on the motorway networks where they provide point speed and traffic volumes. Models have been proposed for temporal and spatial generalization of speed for average travel time estimation. Advancement in technology provides complementary data sources such as Bluetooth MAC Scanner (BMS), detecting the MAC ID of the Bluetooth devices transported by the traveller. Matching the data from two BMS stations provides individual vehicle travel time. Generally, on the motorways loops are closely spaced, whereas BMS are placed few kilometres apart. In this research, we fuse BMSs and loops data to define the trajectories of the Bluetooth vehicles. The trajectories are utilised to estimate the travel time statistics between any two points along the motorway. The proposed model is tested using simulation and validated with real data from Pacific motorway, Brisbane. Comparing the model with the linear interpolation based trajectory provides significant improvements.