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Samantha Lowchoy

Samantha Lowchoy
Griffith University, Mount Gravatt Campus, Australia · Social and Behavioural Sciences Research College

PhD

About

54
Publications
10,428
Reads
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3,026
Citations
Citations since 2016
3 Research Items
1746 Citations
2016201720182019202020212022050100150200250
2016201720182019202020212022050100150200250
2016201720182019202020212022050100150200250
2016201720182019202020212022050100150200250
Additional affiliations
April 2004 - February 2015
Queensland University of Technology
Position
  • Statistical Consultant, Postdoctoral Research Fellow, Senior Research Fellow, Lecturer
April 2004 - March 2015
Queensland University of Technology
Position
  • Postgraduate Research Fellow, Senior Research Fellow (CRCNPB), ECARD Lecturer
December 1999 - April 2004
Queensland Environmental Protection Agency
Position
  • Senior Environmental Officer (Modeller), Principal Environmental Officer (Modeller), Senior Principal Environmental Officer (Environmetrician)

Publications

Publications (54)
Article
Inclusive Indigenous Education is geared towards shifting worldviews, sharing agendas, and preparing social-justice-oriented educators. With this comes the expectation that pre-service teachers will leave supportive education programs prepared to teach sensitive issues related to Indigeneity. Yet, with the onset of COVID-19, systemic changes were m...
Article
This experimental article provides an immanent alternative to the neo-positivist outcomes-driven turn currently cannibalising the Academy. It offers a stitched together, multiphrenic creature, formed in darkness, gore and toil; a co-generative performance embodying coming-to-know as a process of creative co-inquiry. It writes into existence an unga...
Article
Bayesian methods provide a more general approach to statistical analysis that mathematically includes Null Hypothesis Significance Testing (NHST) and classical statistical modelling as special cases. This expanded, Bayesian, approach provides several benefits, which we illustrate using a case study about decision-making by teachers. We focus on a r...
Conference Paper
Full-text available
Species distribution modelling (SDM) typically analyses species’ presence together with some form of absence information. Ideally absences comprise observations or are inferred from comprehensive sampling. When such information is not available, then pseudo-absences are often generated from the background locations within the study region of intere...
Article
Full-text available
When limited or no observed data are available, it is often useful to obtain expert knowledge about parameters of interest, including point estimates and the uncertainty around these values. However, it is vital to elicit this information appropriately in order to obtain valid estimates. This is particularly important when the experts' uncertainty...
Article
Motivated by the analysis of the Australian Grain Insect Resistance Database (AGIRD), we develop a Bayesian hurdle modelling approach to assess trends in strong resistance of stored grain insects to phosphine over time. The binary response variable from AGIRD indicating presence or absence of strong resistance is characterized by a majority of abse...
Article
Introduced in this paper is a Bayesian model for isolating the resonant frequency from combustion chamber resonance. The model shown in this paper focused on characterising the initial rise in the resonant frequency to investigate the rise of in-cylinder bulk temperature associated with combustion. By resolving the model parameters, it is possible...
Article
Global species richness, whether estimated by taxon, habitat, or ecosystem, is a key biodiversity metric. Yet, despite the global importance of biodiversity and increasing threats to it (e.g., [1-4]), we are no better able to estimate global species richness now than we were six decades ago [5]. Estimates of global species richness remain highly un...
Poster
Full-text available
Heuristics and biases play a major role in designing expert elicitations. The effect they have on the process of elicitations can alter the results. When framing elicitations, we should be equally concerned with not only what we ask experts to assess, but also how we ask it. There is considerable amount of research done in the field of psychology o...
Article
Full-text available
Recently, attempts to improve decision making in species management have focussed on uncertainties associated with modelling temporal fluctuations in populations. Reducing model uncertainty is challenging; while larger samples improve estimation of species trajectories and reduce statistical errors, they typically amplify variability in observed tr...
Article
Full-text available
Expert knowledge is a valuable source of information with a wide range of research applications. Despite the recent advances in defining expert knowledge, little attention has been given to how to view expertise as a system of interacting contributory factors for quantifying an individual's expertise. We present a systems approach to expertise that...
Data
Validity assessment for expert elicited Bayesian Networks.
Article
A novel in-cylinder pressure method for determining ignition delay has been proposed and demonstrated. This method proposes a new Bayesian statistical model to resolve the start of combustion, defined as being the point at which the band-pass in-cylinder pressure deviates from background noise and the combustion resonance begins. Further, it is dem...
Chapter
Introduction Models and methods Case studies Conclusion References
Chapter
Priors in the very beginning Methodology I: Priors defined by mathematical criteria Methodology II: Modelling informative priors Case studies Discussion Acknowledgements References
Article
Full-text available
We consider the problem of combining opinions from different experts in an explicitly model-based way to construct a valid subjective prior in a Bayesian statistical approach. We propose a generic approach by considering a hierarchical model accounting for various sources of variation as well as accounting for potential dependence between experts....
Article
Full-text available
Observational time series data often exhibit both cyclic temporal trends and autocorrelation and may also depend on covariates. As such, there is a need for flexible regression models that are able to capture these trends and model any residual autocorrelation simultaneously. Modelling the autocorrelation in the residuals leads to more realistic fo...
Article
Bayesian networks (BNs) are becoming increasingly common in problems with spatial aspects. The degree of spatial involvement may range from spatial mapping of BN outputs based on nodes in the BN that explicitly involve geographic features, to integration of different networks based on geographic information. In these situations, it is useful to con...
Article
Full-text available
This paper outlines a methodology for semi-parametric spatio-temporal modelling of data which is dense in time but sparse in space, obtained from a split panel design, the most feasible approach to covering space and time with limited equipment. The data are hourly averaged particle number concentration (PNC) and were collected, as part of the Ultr...
Article
Elicitation of expert knowledge has proven to be useful in a variety of disciplines including ecology, conservation management and policy. Here we report the development of a protocol and software tool that aids elicitation of expert knowledge of complex systems of count data, focusing on a case study of elicitation of species richness estimates fo...
Article
Full-text available
Expert knowledge is used widely in the science and practice of conservation because of the complexity of problems, relative lack of data, and the imminent nature of many conservation decisions. Expert knowledge is substantive information on a particular topic that is not widely known by others. An expert is someone who holds this knowledge and who...
Chapter
Expert elicitation is the process of determining what expert knowledge is relevant to support a quantitative analysis and then eliciting this information in a form that supports analysis or decision-making. The credibility of the overall analysis, therefore, relies on the credibility of the elicited knowledge. This, in turn, is determined by the ri...
Chapter
Conservation planning and management programs typically assume relatively homogeneous ecological landscapes. Such “ecoregions” serve multiple purposes: they support assessments of competing environmental values, reveal priorities for allocating scarce resources, and guide effective on-ground actions such as the acquisition of a protected area and h...
Article
In this paper, we compare the Generalised Linear Model (GLM) and Generalised Additive Model (GAM) for modelling the particle number concentration (PNC) of outdoor, airborne ultrafine particles in Helsinki, Finland. We examine temporal trends in PNC and examine the relationship between PNC and rainfall, wind speed and direction, humidity, temperatur...
Article
Full-text available
Classification and regression tree (CART) models are tree-based exploratory data analysis methods which have been shown to be very useful in identifying and estimating complex hierarchical relationships in ecological and medical contexts. In this paper, a Bayesian CART model is described and applied to the problem of modelling the cryptosporidiosis...
Article
When modelling the distribution of a species, it is often not possible to comprehensively sample the whole distribution of the species and managers may have habitat models based on data from one area that they want to apply in other areas. Hence, an important question is: how accurate are models of the distributions of species when applied beyond t...
Article
The aim of this review is to explore the methodologies employed to assess the exposure of children to air pollutants, in particular traffic emissions, at school, and how these methodologies influence the assessment of the impact of this exposure on the children’s health. This involves four main steps: the measurement of air quality at school level,...
Article
Full-text available
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...
Article
Habitat models are widely used in ecology, however there are relatively few studies of rare species, primarily because of a paucity of survey records and lack of robust means of assessing accuracy of modelled spatial predictions. We investigated the potential of compiled ecological data in developing habitat models for Macadamia integrifolia, a vul...
Article
Full-text available
Expert elicitation is the process of retrieving and quantifying expert knowledge in a particular domain. Such information is of particular value when the empirical data is expensive, limited or unreliable. This paper describes a new software tool, called Elicitator, which assists in quantifying expert knowledge in a form suitable for use as a prior...
Conference Paper
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...
Article
1. Species’ distribution modelling relies on adequate data sets to build reliable statistical models with high predictive ability. However, the money spent collecting empirical data might be better spent on management. A less expensive source of species’ distribution information is expert opinion. This study evaluates expert knowledge and its sourc...
Article
Full-text available
Numerous expert elicitation methods have been suggested for generalised linear models (GLMs). This paper compares three relatively new approaches to eliciting expert knowledge in a form suitable for Bayesian logistic regression. These methods were trialled on two experts in order to model the habitat suitability of the threatened Australian brush-t...
Article
Bayesian statistical modeling has several benefits within an ecological context. In particular, when observed data are limited in sample size or representativeness, then the Bayesian framework provides a mechanism to combine observed data with other "prior" information. Prior information may be obtained from earlier studies, or in their absence, fr...
Article
Full-text available
In any statistical analysis the adopted model should be chosen to suit the aim of the analysis. An example in rare event modeling might be the description of tail behavior in a distribution. In these situations it may be useful to combine several distinct model choice criteria which emphasize different aspects of model-fit in discriminating amongst...
Article
Full-text available
Expert knowledge is valuable in many modelling endeavours, particularly where data is not extensive or sufficiently robust. In Bayesian statistics, expert opinion may be formulated as informative priors, to provide an honest reflection of the current state of knowledge, before updating this with new information. Technology is increasingly being exp...
Article
Development of anthracnose caused by Cotletotrichum gloeosporioides in mixtures of the tropical pasture legume Stylosanthes was studied in 3 successive years. The performance of three accessions of Stylosanthes sp., 36260, QiaO42 and 55860 and cv. Seca were evaluated by growing these in three different mixtures with other susceptible or resistant c...
Article
Determining the ecologically relevant spatial scales for predicting species occurrences is an important concept when determining species–environment relationships. Therefore species distribution modelling should consider all ecologically relevant spatial scales. While several recent studies have addressed this problem in artificially fragmented lan...
Article
Often only limited information can be elicited from experts about a distribution, such as quantiles or other summary statistics. Skewed non-negative distributions often arise in practice, and present a particular challenge for elicitation due to their asymmetry. This paper provides a range of simple approaches to encoding these types of distributio...
Article
An expert elicitation approach for Bayesian classification trees is developed in this paper. This approach is illustrated for habitat suitability modelling of the threatened Australian brush-tailed rock-wallaby Petrogale penicillata, in which the opinion of one expert is elicited. In the ecological field, expert opinion has been acknowledged as pro...
Article
Full-text available
A common feature of ecological data sets is their tendency to contain many zero values. Statistical inference based on such data are likely to be inefficient or wrong unless careful thought is given to how these zeros arose and how best to model them. In this paper, we propose a framework for understanding how zero-inflated data sets originate and...
Article
Full-text available
This paper provides a brief review of the more popular methods for comparing models in a Bayesian framework. Personal experience in implementing these methods in problems requiring mixture models is also referenced.
Article
Ross River virus (RRv), also known as Epidemic Polyarthritis, is a debilitating disease and is the most prevalent vector-borne disease in Australia (Lin et al. 2002). The virus can survive and replicate in humans and other vertebrae hosts, and is transmitted by a variety of mosquito vectors (Russell and Dwyer 2000). The disease in humans is nonfata...
Article
Full-text available
Ecological regions are increasingly used as a spatial unit for planning and environmental management. It is important to define these regions in a scientifically defensible way to justify any decisions made on the basis that they are representative of broad environmental assets. The paper describes a methodology and tool to identify cohesive bioreg...
Article
Accounting of carbon stocks in woody vegetation for greenhouse purposes requires definition of medium term trends with accurate error assessment. Tree and shrub cover was sampled through time at randomly located sites over a large area of central Queensland, Australia using aerial photography from 1945 to 1999. Calibration models developed from fie...
Article
Ecological regions are increasingly used as a spatial unit for planning and environmental management. It is important to define these regions in a scientifically defensible way to justify any decisions made on the basis that they are representative of broad environmental assets. The paper describes a methodology and tool to identify cohesive bioreg...
Article
A paraître dans "Bayesian Statistics 9", Oxford University Press. Within the Bayesian paradigm, expert knowledge is typically used to construct informative priors, with an emphasis on combination with empirical data to form posterior estimates. In pioneering research, however, the initial step of represent- ing the current state of knowledge may de...

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