A new approach to spatial data interpolation using higher-order statistics

Interpolation techniques for spatial data have been applied frequently in various fields of geosciences. Although most conventional interpolation methods assume that it is sufficient to use first- and second-order statistics to characterize random fields, researchers have now realized that these methods cannot always provide reliable interpolation results, since geological and environmental phenomena tend to be very complex, presenting non-Gaussian distribution and/or non-linear inter-variable relationship. This paper proposes a new approach to the interpolation of spatial data, which can be applied with great flexibility. Suitable cross-variable higher-order spatial statistics are developed to measure the spatial relationship between the random variable at an unsampled location and those in its neighbourhood. Given the computed cross-variable higher-order spatial statistics, the conditional probability density function (CPDF) is approximated via polynomial expansions, which is then utilized to determine the interpolated value at the unsampled location as an expectation. In addition, the uncertainty associated with the interpolation is quantified by constructing prediction intervals of interpolated values. The proposed method is applied to a mineral deposit dataset, and the results demonstrate that it outperforms kriging methods in uncertainty quantification. The introduction of the cross-variable higher-order spatial statistics noticeably improves the quality of the interpolation since it enriches the information that can be extracted from the observed data, and this benefit is substantial when working with data that are sparse or have non-trivial dependence structures.

Estimating the burden of disease attributable to smoking in South Africa in 2000

Objectives To quantify the burden of disease attributable to smoking in South Africa for 2000. Design The absolute difference between observed lung cancer death rate and the level in non-smokers, adjusted for occupational and indoor exposure to lung carcinogens, was used to estimate the proportion of lung cancer deaths attributable to smoking and the smoking impact ratio (SIR). The SIR was substituted for smoking prevalence in the attributable fraction formula for chronic obstructive pulmonary disease (COPD) and cancers to allow for the long lag between exposure and outcome. Assuming a shorter lag between exposure and disease, the current prevalence of smoking was used to estimate the population-attributable fractions (PAF) for the other outcomes. Relative risks (RR) from the American Cancer Society cancer prevention study (CPS-II) were used to calculate PAF. Setting South Africa. Outcome measures Deaths and disability-adjusted life years (DALYs) due to lung and other cancers, COPD, cardiovascular conditions, respiratory tuberculosis, and other respiratory and medical conditions. Results Smoking caused between 41 632 and 46 656 deaths in South Africa, accounting for 8.0 - 9.0% of deaths and 3.7 - 4.3% of DALYs in 2000. Smoking ranked third (after unsafe sex/sexually transmitted disease and high blood pressure) in terms of mortality among 17 risk factors evaluated. Three times as many males as females died from smoking. Lung cancer had the largest attributable fraction due to smoking. However, cardiovascular diseases accounted for the largest proportion of deaths attributed to smoking. Conclusion Cigarette smoking accounts for a large burden of preventable disease in South Africa. While the government has taken bold legislative action to discourage tobacco use since 1994, it still remains a major public health priority.

Phenotyping cotton ovule fibre initiation with spatial statistics

Yield in cultivated cotton (Gossypium spp.) is affected by the number and distribution of fibres initiated on the seed surface but, apart from simple statistical summaries, little has been done to assess this phenotype quantitatively. Here we use two types of spatial statistics to describe and quantify differences in patterning of cotton ovule fibre initials (FI). The following five different species of Gossypium were analysed: G. hirsutum L., G. barbadense L., G. arboreum, G. raimondii Ulbrich. and G. trilobum (DC.) Skovsted. Scanning electron micrographs of FIs were taken on the day of anthesis. Cell centres for fibre and epidermal cells were digitised and analysed by spatial statistics methods appropriate for marked point processes and tessellations. Results were consistent with previously published reports of fibre number and spacing. However, it was shown that the spatial distributions of FIs in all of species examined exhibit regularity, and are not completely random as previously implied. The regular arrangement indicates FIs do not appear independently of each other and we surmise there may be some form of mutual inhibition specifying fibre-initial development. It is concluded that genetic control of FIs differs from that of stomata, another well studied plant idioblast. Since spatial statistics show clear species differences in the distribution of FIs within this genus, they provide a useful method for phenotyping cotton. © CSIRO 2007.

Statistics at play

Three core components in developing children’s understanding and appreciation of data — establish a context, pose and answer statistical questions, represent and interpret data — lay the foundation for the fourth component: use data to enhance existing context.

Public health interventions for increasing physical activity in children, adolescents and adults : an overview of systematic reviews

This is the protocol for a review and there is no abstract. The objectives are as follows: This overview intends to: a) summarise the existing evidence on interventions that aim to increase PA; b) explore whether any effects of the intervention are different within and between populations, and whether these differences form an equity gradient such as an effect that differs according the advantage/disadvantage (e.g. low income and ethnic minorities); c) highlight gaps in the present evidence base that may warrant a Cochrane systematic review to be completed; and c) identify 'up to date' Cochrane reviews. .

A meta-analysis of the correlation between heritage language and ethnic identity

The interaction between heritage language (HL) and ethnic identity has gained increasing scholarly attention over the past decades. Numerous quantitative studies have investigated and vindicated this interaction within certain contexts. Nevertheless, quantitative evidence on this interaction across contexts is absent to date. The current meta-analysis aims to make a contribution in this regard. By integrating relevant studies, this meta-analysis presents a powerful estimation of the reality in relation to the interaction between HL and ethnic identity. By virtue of certain retrieval strategies and selection criteria, the meta-analysis includes 43 data-sets emerging from 18 studies that have addressed the statistical correlation between the proficiency of HL and the sense of ethnic identity associated with different ethnic groups. When contrasted to one another, the results of these included studies are significantly different. However, when combined together, these studies point to a statistically significant moderate positive correlation between sense of ethnic identity and proficiency of HL across different ethnic groups. This result has a medium effect. The meta-analysis also inspires some methodological and theoretical discussions.

The whole world shook : shifts in ethnic, national and heroic identities in children's fiction about 9/11

Like many other cataclysmic events September 11, a day now popularly believed to have 'changed the world', has become a topic taken up by children's writers. This thesis, titled The Whole World Shook: Ethnic, National and Heroic Identities in Children's Fiction About 9/11, examines how cultural identities are constructed within fictional texts for young people written about the attacks on the Twin Towers. It identifies three significant identity categories encoded in 9/11 books for children: ethnic identities, national identities, and heroic identities. The thesis argues that the identities formed within the selected children's texts are in flux, privileging performances of identities that are contingent on post-9/11 politics. This study is located within the field of children's literature criticism, which supports the understanding that children's books, like all texts, play a role in the production of identities. Children's literature is highly significant both in its pedagogical intent (to instruct and induct children into cultural practices and beliefs) and in its obscurity (in making the complex simple enough for children, and from sometimes intentionally shying away from difficult things). This literary criticism informed the study that the texts, if they were to be written at all, would be complex, varied and most likely as ambiguous and contradictory as the responses to the attacks on New York themselves. The theoretical framework for this thesis draws on a range of critical theories including literary theory, cultural studies, studies of performativity and postmodernism. This critical framework informs the approach by providing ways for: (i) understanding how political and ideological work is performed in children's literature; (ii) interrogating the constructed nature of cultural identities; (iii) developing a nuanced methodology for carrying out a close textual analysis. The textual analysis examines a representative sample of children's texts about 9/11, including picture books, young adult fiction, and a selection of DC Comics. Each chapter focuses on a different though related identity category. Chapter Four examines the performance of ethnic identities and race politics within a sample of picture books and young adult fiction; Chapter Five analyses the construction of collective, national identities in another set of texts; and Chapter Six does analytic work on a third set of texts, demonstrating the strategic performance of particular kinds of heroic identities. I argue that performances of cultural identities constructed in these texts draw on familiar versions of identities as well as contribute to new ones. These textual constructions can be seen as offering some certainties in increasingly uncertain times. The study finds, in its sample of books a co-mingling of xenophobia and tolerance; a binaried competition between good and evil and global harmony and national insularity; and a lauding of both the commonplace hero and the super-human. Being a recent corpus of texts about 9/11, these texts provide information on the kinds of 'selves' that appear to be privileged in the West since 2001. The thesis concludes that the shifting identities evident in texts that are being produced for children about 9/11 offer implicit and explicit accounts of what constitute good citizenship, loyalty to nation and community, and desirable attributes in a Western post-9/11 context. This thesis makes an original contribution to the field of children's literature by providing a focussed and sustained analysis of how texts for children about 9/11 contribute to formations of identity in these complex times of cultural unease and global unrest.

Summarising and reporting sugarcane locomotive run statistics from TOTools and GPS data

The majority of sugar mill locomotives are equipped with GPS devices from which locomotive position data is stored. Locomotive run information (e.g. start times, run destinations and activities) is electronically stored in software called TOTools. The latest software development allows TOTools to interpret historical GPS information by combining this data with run information recorded in TOTools and geographic information from a GIS application called MapInfo. As a result, TOTools is capable of summarising run activity details such as run start and finish times and shunt activities with great accuracy. This paper presents 15 reports developed to summarise run activities and speed information. The reports will be of use pre-season to assist in developing the next year's schedule and for determining priorities for investment in the track infrastructure. They will also be of benefit during the season to closely monitor locomotive run performance against the existing schedule.

How do experts think about statistics? Hints for improving undergraduate and postgraduate training

Experts are increasingly being called upon to quantify their knowledge, particularly in situations where data is not yet available or of limited relevance. In many cases this involves asking experts to estimate probabilities. For example experts, in ecology or related fields, might be called upon to estimate probabilities of incidence or abundance of species, and how they relate to environmental factors. Although many ecologists undergo some training in statistics at undergraduate and postgraduate levels, this does not necessarily focus on interpretations of probabilities. More accurate elicitation can be obtained by training experts prior to elicitation, and if necessary tailoring elicitation to address the expert’s strengths and weaknesses. Here we address the first step of diagnosing conceptual understanding of probabilities. We refer to the psychological literature which identifies several common biases or fallacies that arise during elicitation. These form the basis for developing a diagnostic questionnaire, as a tool for supporting accurate elicitation, particularly when several experts or elicitors are involved. We report on a qualitative assessment of results from a pilot of this questionnaire. These results raise several implications for training experts, not only prior to elicitation, but more strategically by targeting them whilst still undergraduate or postgraduate students.

Assessment of body composition of Sri Lankan Australian children using ethnic specific equations

Since ethnic differences exist in body composition, assessment methods need to be validated prior to use in different populations. This study attempts to validate the use of Sri Lankan based body composition assessment tools on a group of 5 - 15 year old Australian children of Sri Lankan origin. The study was conducted at the Body Composition Laboratory of the Children’s Nutrition Research Centre at the Royal Children’s Hospital, Brisbane, Australia. Height (Ht), weight (Wt), segmental length (Lsegment name) and skinfold thickness (SFT) were measured. The whole body and segmental bio impedance analysis (BIA) were also measured. The body composition determined by the deuterium dilution technique (criterion method) was compared with the assessments done using prediction equations developed on Sri Lankan children. 27 boys and 15 girls were studied. All predictions of body composition parameters, except percentage fat mass (FM) assessed by the SFT-FM equation in girls gave statistically significant correlations with the criterion method. They had a low mean bias and most were not influenced by the measured parameter. Although living in a different socioeconomic state, the equations developed on children of the same ethnic background gives a better predictive value of body composition. This highlights the ethnic influence on body composition.

Association of variants in MMEL1 and CTLA4 with rheumatoid arthritis in the Han Chinese population

Background: The genome-wide association study era has made great progress in identifying susceptibility genes and genetic loci for rheumatoid arthritis (RA) in populations of White European ancestry. However, few studies have tried to dissect disease aetiopathogenesis in other ethnic populations. Objective: To investigate these associations in the Han Chinese population. Methods: Haplotypes from the HapMap database Chinese population were used to select tag-single-nucleotide polymorphisms (SNPs) (r2 =0.8) across 19 distinct RA genomic regions. A two phase case-control association study was performed, with 169 SNPs genotyped in phase I (n=571 cases, n=880 controls), and 64 SNPs achieving p<0.2 in the first phase being genotyped in phase II (n=464 cases, n=822 controls). Association statistics were calculated using permutation tests both unadjusted and adjusted for the number of markers studied. Results: Robust association was detected for MMEL1 and CTLA4 , and modest association was identified for another six loci: PADI4 , STAT4 , PRDM1 , CDK6 , TRAF1-C5 and KIF5A-PIP4K2C. All three markers genotyped in MMEL1 demonstrated association, with peak signal for rs3890745 (p=2.6×10 -5unadjusted, p=0.003 adjusted, OR=0.79). For CTLA4 , significance was detected for three of five variants showing association, with peak association for marker rs12992492 (p=4.3×10-5 unadjusted, p=0.0021 adjusted, OR=0.77). Lack of association of common variants in PTPN22 with RA in Han Chinese was confirmed. Conclusion: This study identifies MMEL1 and CTLA4 as RA susceptibility genes, provides suggestive evidence of association for a further six loci in the Han Chinese population and confirms lack of PTPN22 association in Asian populations. It also confirms the value of multiethnic population studies to help dissect disease aetiopathogenesis.

Social capital or ethnic enclave location? A multilevel explanation of immigrant business growth

The rapid increase in migration into host countries and the growth of immigrant-owned business enterprises has revitalized research on ethnic business. Does micro (individual)-level social capital, or meso (group)-level location within the ethnic enclave lead to immigrant business growth? Or do you need both? We analyze quantitative data collected from 110 Chinese restaurants in Australia, a major host country. At the micro level we find that coethnic (same ethnic group) networks are critical to the growth of an immigrant entrepreneur's business, particularly in the early years. But non-coethnic (different ethnic group) social capital only has a positive impact on business growth for immigrant businesses outside the ethnic enclave. Our findings are relevant, not only to host-country policymakers, but also for future immigrant business owners and ethnic community leaders trying to better understand how to promote healthy communities and sustainable economic growth.

Introducing the practice of statistics: are we environmentally friendly?

The practice of statistics is the focus of the world in which professional statisticians live. To understand meaningfully what this practice is about, students need to engage in it themselves. Acknowledging the limitations of a genuine classroom setting, this study attempted to expose four classes of year 5 students (n=91) to an authentic experience of the practice of statistics. Setting an overall context of people’s habits that are considered environmentally friendly, the students sampled their class and set criteria for being environmentally friendly based on questions from the Australian Bureau of Statistics CensusAtSchool site. They then analysed the data and made decisions, acknowledging their degree of certainty, about three populations based on their criteria: their class, year 5 students in their school and year 5 students in Australia. The next step was to collect a random sample the size of their class from an Australian Bureau of Statistics ‘population’, analyse it and again make a decision about Australian year 5 students. At the end, they suggested what further research they might do. The analysis of students’ responses gives insight into primary students’ capacity to appreciate and understand decision making, and to participate in the practice of statistics, a topic that has received very little attention in the literature. Based on the total possible score of 23 from student workbook entries, 80 % of students achieved at least a score of 11.

Inferential, non-parametric statistics to assess quality of probabilistic forecast systems

Many statistical forecast systems are available to interested users. In order to be useful for decision-making, these systems must be based on evidence of underlying mechanisms. Once causal connections between the mechanism and their statistical manifestation have been firmly established, the forecasts must also provide some quantitative evidence of `quality’. However, the quality of statistical climate forecast systems (forecast quality) is an ill-defined and frequently misunderstood property. Often, providers and users of such forecast systems are unclear about what ‘quality’ entails and how to measure it, leading to confusion and misinformation. Here we present a generic framework to quantify aspects of forecast quality using an inferential approach to calculate nominal significance levels (p-values) that can be obtained either by directly applying non-parametric statistical tests such as Kruskal-Wallis (KW) or Kolmogorov-Smirnov (KS) or by using Monte-Carlo methods (in the case of forecast skill scores). Once converted to p-values, these forecast quality measures provide a means to objectively evaluate and compare temporal and spatial patterns of forecast quality across datasets and forecast systems. Our analysis demonstrates the importance of providing p-values rather than adopting some arbitrarily chosen significance levels such as p < 0.05 or p < 0.01, which is still common practice. This is illustrated by applying non-parametric tests (such as KW and KS) and skill scoring methods (LEPS and RPSS) to the 5-phase Southern Oscillation Index classification system using historical rainfall data from Australia, The Republic of South Africa and India. The selection of quality measures is solely based on their common use and does not constitute endorsement. We found that non-parametric statistical tests can be adequate proxies for skill measures such as LEPS or RPSS. The framework can be implemented anywhere, regardless of dataset, forecast system or quality measure. Eventually such inferential evidence should be complimented by descriptive statistical methods in order to fully assist in operational risk management.