Quantile regression without the curse of unsmoothness

We consider quantile regression models and investigate the induced smoothing method for obtaining the covariance matrix of the regression parameter estimates. We show that the difference between the smoothed and unsmoothed estimating functions in quantile regression is negligible. The detailed and simple computational algorithms for calculating the asymptotic covariance are provided. Intensive simulation studies indicate that the proposed method performs very well. We also illustrate the algorithm by analyzing the rainfall–runoff data from Murray Upland, Australia.

Infertility, medical advice and treatment with fertility hormones and/or in vitro fertilisation: a population perspective from the Australian Longitudinal Study on Women's Health

OBJECTIVE: To identify the factors associated with infertility, seeking advice and treatment with fertility hormones and/or in vitro fertilisation (IVF) among a general population of women. METHODS: Participants in the Australian Longitudinal Study on Women's Health aged 28-33 years in 2006 had completed up to four mailed surveys over 10 years (n=9,145). Parsimonious multivariate logistic regression was used to identify the socio-demographic, biological (including reproductive histories), and behavioural factors associated with infertility, advice and hormonal/IVF treatment. RESULTS: For women who had tried to conceive or had been pregnant (n=5,936), 17% reported infertility. Among women with infertility (n=1031), 72% (n=728) sought advice but only 50% (n=356) used hormonal/IVF treatment. Women had higher odds of infertility when: they had never been pregnant (OR=7.2, 95% CI 5.6-9.1) or had a history of miscarriage (OR range=1.5-4.0) than those who had given birth (and never had a miscarriage or termination). CONCLUSION: Only one-third of women with infertility used hormonal and/or IVF treatment. Women with PCOS or endometriosis were the most proactive in having sought advice and used hormonal/IVF treatment. IMPLICATIONS: Raised awareness of age-related declining fertility is important for partnered women aged approximately 30 years to encourage pregnancy during their prime reproductive years and reduce the risk of infertility.

Therapeutic immunisation of rabbits with cottontail rabbit papillomavirus (CRPV) virus-like particles (VLP) induces regression of established papillomas

There is overwhelming evidence that persistent infection with high-risk human papillomaviruses (HR-HPV) is the main risk factor for invasive cancer of the cervix. Due to this global public health burden, two prophylactic HPV L1 virus-like particles (VLP) vaccines have been developed. While these vaccines have demonstrated excellent type-specific prevention of infection by the homologous vaccine types (high and low risk HPV types), no data have been reported on the therapeutic effects in people already infected with the low-risk HPV type. In this study we explored whether regression of CRPV-induced papillomas could be achieved following immunisation of out-bred New Zealand White rabbits with CRPV VLPs. Rabbits immunised with CRPV VLPs had papillomas that were significantly smaller compared to the negative control rabbit group (P ≤ 0.05). This data demonstrates the therapeutic potential of PV VLPs in a well-understood animal model with potential important implications for human therapeutic vaccination for low-risk HPVs. © 2008 Govan et al; licensee BioMed Central Ltd.

Regression and hypothesis tests for multivariate GNSS state time series

A satellite based observation system can continuously or repeatedly generate a user state vector time series that may contain useful information. One typical example is the collection of International GNSS Services (IGS) station daily and weekly combined solutions. Another example is the epoch-by-epoch kinematic position time series of a receiver derived by a GPS real time kinematic (RTK) technique. Although some multivariate analysis techniques have been adopted to assess the noise characteristics of multivariate state time series, statistic testings are limited to univariate time series. After review of frequently used hypotheses test statistics in univariate analysis of GNSS state time series, the paper presents a number of T-squared multivariate analysis statistics for use in the analysis of multivariate GNSS state time series. These T-squared test statistics have taken the correlation between coordinate components into account, which is neglected in univariate analysis. Numerical analysis was conducted with the multi-year time series of an IGS station to schematically demonstrate the results from the multivariate hypothesis testing in comparison with the univariate hypothesis testing results. The results have demonstrated that, in general, the testing for multivariate mean shifts and outliers tends to reject less data samples than the testing for univariate mean shifts and outliers under the same confidence level. It is noted that neither univariate nor multivariate data analysis methods are intended to replace physical analysis. Instead, these should be treated as complementary statistical methods for a prior or posteriori investigations. Physical analysis is necessary subsequently to refine and interpret the results.

Spontaneous Volunteering During Natural Disasters

The recent spate of natural disasters across Australia has led to an outpouring of spontaneous volunteering, both formally through nonprofit and government agencies and informally through local community and online networks. Relatively little is understood about the motivations and characteristics of spontaneous volunteers. The aims of this project were to:  Examine the characteristics and motivations of spontaneous volunteers who respond to a crisis event;  Illuminate the effects of spontaneous volunteering on personal, social and civic networks;  Explicate the conditions under which sustained volunteering and other forms of civic engagement arise from spontaneous volunteering and;  Consider the practical implications of these findings for organisations involved in coordinating volunteers both with and beyond disaster events.

Gradual training of cascaded shape regression for facial landmark localization and pose estimation

Facial landmarks play an important role in face recognition. They serve different steps of the recognition such as pose estimation, face alignment, and local feature extraction. Recently, cascaded shape regression has been proposed to accurately locate facial landmarks. A large number of weak regressors are cascaded in a sequence to fit face shapes to the correct landmark locations. In this paper, we propose to improve the method by applying gradual training. With this training, the regressors are not directly aimed to the true locations. The sequence instead is divided into successive parts each of which is aimed to intermediate targets between the initial and the true locations. We also investigate the incorporation of pose information in the cascaded model. The aim is to find out whether the model can be directly used to estimate head pose. Experiments on the Annotated Facial Landmarks in the Wild database have shown that the proposed method is able to improve the localization and give accurate estimates of pose.

Factors associated with common mental disorders during the transition to adulthood : do emerging adults and ‘early starters’ differ? Findings from an Australian birth cohort study

Background: Despite increasing diversity in pathways to adulthood, choices available to young people are influenced by environmental, familial and individual factors, namely access to socioeconomic resources, family support and mental and physical health status. Young people from families with higher socioeconomic position (SEP) are more likely to pursue tertiary education and delay entry to adulthood, whereas those from low socioeconomic backgrounds are less likely to attain higher education or training, and more likely to partner and become parents early. The first group are commonly termed ‘emerging adults’ and the latter group ‘early starters’. Mental health disorders during this transition can seriously disrupt psychological, social and academic development as well as employment prospects. Depression, anxiety and most substance use disorders have early onset during adolescence and early adulthood with approximately three quarters of lifetime psychiatric disorders having emerged by 24 years of age. Aims: This thesis aimed to explore the relationships between mental health, sociodemographic factors and family functioning during the transition to adulthood. Four areas were investigated: 1) The key differences between emerging adults and ‘early starters’, were examined and focused on a series of social, economic, and demographic factors as well as DSM-IV diagnoses; 2) Methodological issues associated with the measurement of depression and anxiety in young adults were explored by comparing a quantitative measure of symptoms of anxiety and depression (Achenbach’s YSR and YASR internalising scales) with DSM-IV diagnosed depression and anxiety. 3) The association between family SEP and DSM-IV depression and anxiety was examined in relation to the different pathways to adulthood. 4) Finally, the association between pregnancy loss, abortion and miscarriage, and DSM-IV diagnoses of common psychiatric disorders was assessed in young women who reported early parenting, experiencing a pregnancy loss, or who had never been pregnant. Methods: Data were taken from the Mater University Study of Pregnancy (MUSP), a large birth cohort started in 1981 in Brisbane, Australia. 7223 mothers and their children were assessed five times, at 6 months, 5, 14 and 21 years after birth. Over 3700 young adults, aged 18 to 23 years, were interviewed at the 21-year phase. Respondents completed an extensive series of self-reported questionnaires and a computerised structured psychiatric interview. Three outcomes were assessed at the 21-year phase. Mental health disorders diagnosed by a computerised structured psychiatric interview (CIDI-Auto), the prevalence of DSM-IV depression, anxiety and substance use disorders within the previous 12-month, during the transition (between ages of 18 and 23 years) or lifetime were examined. The primary outcome “current stage in the transition to adulthood” was developed using a measure conceptually constructed from the literature. The measure was based on important demographic markers, and these defined four independent groups: emerging adults (single with no children and living with parents), and three categories of ‘early starter’, singles (with no children or partner, living independently), those with a partner (married or cohabitating but without children) and parents. Early pregnancy loss was assessed using a measure that also defined four independent groups and was based on pregnancy outcomes in the young women This categorised the young women into those who were never pregnant, women who gave birth to a live child, and women who reported some form of pregnancy loss, either an abortion or a spontaneous miscarriage. A series of analyses were undertaken to test the study aims. Potential confounding and mediating factors were prospectively measured between the child’s birth and the 21-year phase. Binomial and multinomial logistic regression was used to estimate the risk of relevant outcomes, and the associations were reported as odds ratios (OR) and 95% confidence intervals (95%CI). Key findings: The thesis makes a number of important contributions to our understanding of the transition to adulthood, particularly in relation to the mental health consequences associated with different pathways. Firstly, findings from the thesis clearly showed that young people who parented or partnered early fared worse across most of the economic and social factors as well as the common mental disorders when compared to emerging adults. That is, young people who became early parents were also more likely to experience recent anxiety (OR=2.0, 95%CI 1.5-2.8) and depression (OR=1.7, 95%CI 1.1-2.7) than were emerging adults after taking into account a range of confounding factors. Singles and those partnering early also had higher rates of lifetime anxiety and depression than emerging adults. Young people who partnered early, but were without children, had decreased odds of recent depression; this may be due to the protective effect of early marriage against depression. It was also found that young people who form families early had an increased risk of cigarette smoking (parents OR=3.7, 95%CI 2.9-4.8) compared to emerging adults, but not heavy alcohol (parents OR=0.4, 95%CI 0.3-0.6) or recent illicit drug use. The high rates of cigarette smoking and tobacco use disorders in ‘early starters’ were explained by common risk factors related to early adversity and lower SEP. Having a child and early marriage may well function as a ‘turning point’ for some young people, it is not clear whether this is due to a conscious decision to disengage from a previous ‘substance using’ lifestyle or simply that they no longer have the time to devote to such activities because of child caring. In relation to the methodological issues associated with assessing common mental disorders in young adults, it was found that although the Achenbach empirical internalising scales successfully predicted both later DSM-IV depression (YSR OR=2.3, 95%CI 1.7-3.1) and concurrently diagnosed depression (YASR OR=6.9, 95%CI 5.0- 9.5) and anxiety (YASR OR=5.1, 95%CI 3.8- 6.7), the scales discriminated poorly between young people with or without DSM-IV diagnosed mood disorder. Sensitivity values (the proportion of true positives) for the internalising scales were surprisingly low. Only a third of young people with current DSM-IV depression (range for each of the scales was between 34% to 42%) were correctly identified as cases by the YASR internalising scales, and only a quarter with current anxiety disorder (range of 23% to 31%) were correctly identified. Also, use of the DSM-oriented scales increased sensitivity only marginally (for depression between 2-8%, and anxiety between 2-6%) above the standard Achenbach scales. This is despite the fact that the DSM-oriented scales were originally developed to overcome the poor prediction of DSM-IV diagnoses by the Achenbach scales. The internalising scales, both standard and DSM-oriented, were much more effective at identifying young people with comorbid depression and anxiety, with OR’s 10.1 to 21.7 depending on the internalising scale used. SEP is an important predictor of both an early transition to adulthood and the experience of anxiety during that time Family income during adolescence was a strong predictor of early parenting and partnering before age 24 but not early independent living. Compared to families in the upper quintile, young people from families with low income were nearly twice as likely to live with a partner and four times more likely to become parents (OR ranged from 2.6 to 4.0). This association remained after adjusting for current employment and education level. Children raised in low income families were 30% more likely to have an anxiety disorder (OR=1.3, 95%CI 0.9-1.9), but not depression, as young adults when compared to children from wealthier families. Emerging adults and ‘early starters’ from low income families did not differ in their likelihood of having a later anxiety disorder. Young women reporting a pregnancy loss had nearly three times the odds of experiencing a lifetime illicit drug disorder (excluding cannabis) [abortion OR=3.6, 95%CI 2.0-6.7 and miscarriage OR=2.6, 95%CI 1.2-5.4]. Abortion was associated with alcohol use disorder (OR=2.1, 95%CI 1.3- 3.5) and 12-month depression (OR=1.9, 95%CI 1.1- 3.1). These finding suggest that the association identified by Fergusson et al between abortion and later psychiatric disorders in young women may be due to pregnancy loss and not to abortion, per se. Conclusion: Findings from this thesis support the view that young people who parent or partner early have a greater burden of depression and anxiety when compared to emerging adults. As well, young women experiencing pregnancy loss, from either abortion or miscarriage, are more likely to experience depression and anxiety than are those who give birth to a live infant or who have never been pregnant. Depression, anxiety and substance use disorders often go unrecognised and untreated in young people; this is especially true in young people from lower SEP. Early identification of these common mental health disorders is important, as depression and anxiety experienced during the transition to adulthood have been found to seriously disrupt an individual’s social, educational and economic prospects in later life.

Technical efficiency of mainstream airlines and low-cost carriers : New evidence using bootstrap data envelopment analysis truncated regression

Between 2001 and 2005, the US airline industry faced financial turmoil while the European airline industry entered a period of substantive deregulation. Consequently, this opened up opportunities for low-cost carriers to become more competitive in the market. To assess airline performance and identify the sources of efficiency in the immediate aftermath of these events, we employ a bootstrap data envelopment analysis truncated regression approach. The results suggest that at the time the mainstream airlines needed to significantly reorganize and rescale their operations to remain competitive. In the second-stage analysis, the results indicate that private ownership, status as a low-cost carrier, and improvements in weight load contributed to better organizational efficiency.

Maternal exposure to heatwave and preterm birth in Brisbane, Australia

Objective To quantify the short-term effects of maternal exposure to heatwave on preterm birth. Design An ecological study. Setting: A population-based study in Brisbane, Australia. Population All pregnant women who had a spontaneous singleton live birth in Brisbane between November and March in 2000–2010 were studied. Methods Daily data on pregnancy outcomes, meteorological factors, and ambient air pollutants were obtained. The Cox proportional hazards regression model with time-dependent variables was used to examine the short-term impact of heatwave on preterm birth. A series of cut-off temperatures and durations were used to define heatwave. Multivariable analyses were also performed to adjust for socio-economic factors, demographic factors, meteorological factors, and ambient air pollutants. Main outcome measure Spontaneous preterm births. Results The adjusted hazard ratios (HRs) ranged from 1.13 (95% CI 1.03–1.24) to 2.00 (95% CI 1.37–2.91) by using different heatwave definitions, after controlling for demographic, socio-economic, and meteorological factors, and air pollutants. Conclusions Heatwave was significantly associated with preterm birth: the associations were robust to the definitions of heatwave. The threshold temperatures, instead of duration, could be more likely to influence the evaluation of birth-related heatwaves. The findings of this study may have significant public health implications as climate change progresses.

An analysis of regression models for predicting the speed of a wave glider autonomous surface vehicle

An important aspect of robotic path planning for is ensuring that the vehicle is in the best location to collect the data necessary for the problem at hand. Given that features of interest are dynamic and move with oceanic currents, vehicle speed is an important factor in any planning exercises to ensure vehicles are at the right place at the right time. Here, we examine different Gaussian process models to find a suitable predictive kinematic model that enable the speed of an underactuated, autonomous surface vehicle to be accurately predicted given a set of input environmental parameters.

Applying quantile regression for modeling equivalent property damage only crashes to identify accident blackspots

Hot spot identification (HSID) aims to identify potential sites—roadway segments, intersections, crosswalks, interchanges, ramps, etc.—with disproportionately high crash risk relative to similar sites. An inefficient HSID methodology might result in either identifying a safe site as high risk (false positive) or a high risk site as safe (false negative), and consequently lead to the misuse the available public funds, to poor investment decisions, and to inefficient risk management practice. Current HSID methods suffer from issues like underreporting of minor injury and property damage only (PDO) crashes, challenges of accounting for crash severity into the methodology, and selection of a proper safety performance function to model crash data that is often heavily skewed by a preponderance of zeros. Addressing these challenges, this paper proposes a combination of a PDO equivalency calculation and quantile regression technique to identify hot spots in a transportation network. In particular, issues related to underreporting and crash severity are tackled by incorporating equivalent PDO crashes, whilst the concerns related to the non-count nature of equivalent PDO crashes and the skewness of crash data are addressed by the non-parametric quantile regression technique. The proposed method identifies covariate effects on various quantiles of a population, rather than the population mean like most methods in practice, which more closely corresponds with how black spots are identified in practice. The proposed methodology is illustrated using rural road segment data from Korea and compared against the traditional EB method with negative binomial regression. Application of a quantile regression model on equivalent PDO crashes enables identification of a set of high-risk sites that reflect the true safety costs to the society, simultaneously reduces the influence of under-reported PDO and minor injury crashes, and overcomes the limitation of traditional NB model in dealing with preponderance of zeros problem or right skewed dataset.