High Predictive Performance Models via Semi-Parametric Survival Regression. This project will develop novel statistical models for high prediction performance. When applied to help doctor to treat patients, these models allow the users to include gene or other biomarkers for predicting effectiveness of a treatment. When applied to risk management in finance, these models are capable to include an organization's or individual's ongoing finance status to predict, for example, the probability of or ....High Predictive Performance Models via Semi-Parametric Survival Regression. This project will develop novel statistical models for high prediction performance. When applied to help doctor to treat patients, these models allow the users to include gene or other biomarkers for predicting effectiveness of a treatment. When applied to risk management in finance, these models are capable to include an organization's or individual's ongoing finance status to predict, for example, the probability of or time to loan default. Innovative computational methods will be developed for fitting these models. Compared to traditional prediction method, this approach allows greater flexibility while being superior in terms of statistical accuracy and bias. Extensive analyses of healthcare data from diverse fields will be undertaken.Read moreRead less
Development of population-level algorithms for modelling genomic variation and its impact on cellular function in animals and plants. The purpose of this project is to develop mathematical and computational tools which will enable researchers to model high-throughput biological data at the population level. These models will be used to uncover the effect that genetic variation has on the physiology of the cell and the organism.
System to synapse. Biological tissue is studied at the cellular and organ level with ever increasing clarity and sensitivity, but there are limitations in understanding how microscopic changes are manifested in the organ and vice versa. This project will develop new methods to bridge this gap and allow next generation correlative imaging.
Increasing the efficiency and interpretability of stepped wedge trials. Stepped wedge cluster randomised trials are increasingly being used to test interventions, across many disciplines. This project aims to develop highly efficient trial designs and new methods for the estimation of causally interpretable effects when adherence to interventions is not perfect. This project expects to generate new design types that reduce resources required to test interventions, and methods to understand how t ....Increasing the efficiency and interpretability of stepped wedge trials. Stepped wedge cluster randomised trials are increasingly being used to test interventions, across many disciplines. This project aims to develop highly efficient trial designs and new methods for the estimation of causally interpretable effects when adherence to interventions is not perfect. This project expects to generate new design types that reduce resources required to test interventions, and methods to understand how these interventions work. Expected outcomes include tools to help researchers develop cheaper and more appealing trials, tools to estimate causal effects, the methodology underpinning these tools, and new collaborations. This should provide significant benefits by allowing more interventions to be tested and understood.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE190101326
Funder
Australian Research Council
Funding Amount
$391,546.00
Summary
Statistical methods for modelling the pathways between cause and effect. This project aims to develop new biostatistical methods for addressing complex analytic questions that arise in studies of the causes of health, social, educational and other outcomes in the course of human life. These questions concern the pathways that explain how intermediate factors contribute to a statistical relationship between a probable cause of a later outcome. Mathematical and statistical innovation is needed to ....Statistical methods for modelling the pathways between cause and effect. This project aims to develop new biostatistical methods for addressing complex analytic questions that arise in studies of the causes of health, social, educational and other outcomes in the course of human life. These questions concern the pathways that explain how intermediate factors contribute to a statistical relationship between a probable cause of a later outcome. Mathematical and statistical innovation is needed to address them. The expected outcomes include a suite of novel methods designed to evaluate the impact of intervening to modify causal pathways, while also accommodating common complexities of data such as incompleteness. This project should provide major benefits to studies in public health, social sciences and economics.Read moreRead less
Developing mathematical models and statistical methods to understand the dynamics of infectious diseases: stochasticity, structure and inference. Infectious diseases remain a major contributor to mortality and illness worldwide. The potential for future severe pandemics also continues to present a substantial threat to our health and well-being. Mathematics and statistics are increasingly becoming part of the arsenal used by governments to combat the invasion and spread of infectious diseases. I ....Developing mathematical models and statistical methods to understand the dynamics of infectious diseases: stochasticity, structure and inference. Infectious diseases remain a major contributor to mortality and illness worldwide. The potential for future severe pandemics also continues to present a substantial threat to our health and well-being. Mathematics and statistics are increasingly becoming part of the arsenal used by governments to combat the invasion and spread of infectious diseases. In such work, three themes have emerged as having the potential to revolutionise the modelling of infectious diseases: stochasticity, structure (both age and spatial), and inference. This project will develop state-of-the-art techniques, at the interface of these themes, of critical importance to understanding the dynamics of infectious diseases.Read moreRead less
Statistical methods for quantifying variation in spatiotemporal areal data. This project aims to develop new statistical methods for extracting insights into spatial and temporal variation in areal data. These tools will extend the Australian Cancer Atlas which provides small area estimates for 20 cancers across Australia. The project is significant because it will allow government and other organisations to reap dividends from investment in collecting spatial information and it will enable mode ....Statistical methods for quantifying variation in spatiotemporal areal data. This project aims to develop new statistical methods for extracting insights into spatial and temporal variation in areal data. These tools will extend the Australian Cancer Atlas which provides small area estimates for 20 cancers across Australia. The project is significant because it will allow government and other organisations to reap dividends from investment in collecting spatial information and it will enable modelled small-area estimates to be released without compromising confidentiality. The expected outcomes include new statistical knowledge and new insights into cancer. The results will benefit the many disciplines, managers and policy makers that make decisions based on geographic data mapped over space and time. Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE220101226
Funder
Australian Research Council
Funding Amount
$423,000.00
Summary
Testing Effects of Environmental Exposures on Subsequent Human Generations. This project aims to develop new statistical models to determine how environmental exposures in pregnancy, such as smoking, alcohol consumption and diet, can impact the first and second generations of children. The project will fill a void in unbiased tools to disentangle genetic and environmental components in the inheritance of complex traits, and will be the first to determine objectively if and how effects from envir ....Testing Effects of Environmental Exposures on Subsequent Human Generations. This project aims to develop new statistical models to determine how environmental exposures in pregnancy, such as smoking, alcohol consumption and diet, can impact the first and second generations of children. The project will fill a void in unbiased tools to disentangle genetic and environmental components in the inheritance of complex traits, and will be the first to determine objectively if and how effects from environmental exposures can be inherited. Through international collaborations and advanced interdisciplinary approaches, this project will generate new knowledge in the emerging field of multigenerational inheritance to drive the future design of interventions and influence positive behaviours during pregnancy.Read moreRead less
Statistical methods for the analysis of critical care data, with application to the Australian and New Zealand Intensive Care Database. The recent inquiry into Queensland's Bundaberg Base Hospital highlights the need to monitor hospital performance. This project develops new statistical methods to account for uncertainty in the assessment of provider performance and its outcomes will provide government with institutional comparisons for policy and planning.
Binary regression with additive predictors: new statistical theory with healthcare applications. This project will develop new statistical analysis techniques for predicting whether someone is at risk of adverse health outcomes. The project will then apply the new techniques to a large database on heart attacks, leading to new insights into how patient characteristics and treatments affect the chance of dying from a heart attack.